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GE3151 – Problem Solving And Python Programming Syllabus Regulation 2021 Anna University

January 17, 2024 by Raju

Anna University, Subject code – GE3151, deals with the B.E civil Engineering Semester – I Problem Solving And Python Programming Syllabus regulation 2021 relating to affiliated institutions. From here, Students can get assistance in preparing notes to excel in academic performance.

We include every topic of the Problem Solving And Python Programming Syllabus, to understand the subject very well. It will help you to improve your idea of syllabus of GE3151 – Problem Solving And Python Programming Syllabus on your finger tips to go ahead in a clear path of preparation. In this following article Problem Solving And Python Programming Syllabus , will help you, Hope you share with your friends.

If you want to know more about the syllabus of B.E Civil Engineering connected to an affiliated institution’s under four-year undergraduate degree programme. We provide you with a detailed Year-wise, semester-wise, and Subject-wise syllabus in the following link B.E Civil Engineering Syllabus Anna University, Regulation 2021.

Aim Of Concept:

To understand the basics of algorithmic problem-solving.
To learn to solve problems using Python conditionals and loops.
To define Python functions and use function calls to solve problems.
To use Python data structures – lists, tuples, dictionaries to represent complex data.
To do input/output with files in Python.

GE3151 – Problem Solving And Python Programming Syllabus

Unit I: Computational Thinking And Problem Solving

Fundamentals of Computing – Identification of Computational Problems -Algorithms, building blocks of algorithms (statements, state, control flow, functions), notation (pseudo code, flow chart, programming language), algorithmic problem solving, simple strategies for developing algorithms (iteration, recursion). Illustrative problems: find minimum in a list, insert a card in a list of sorted cards, guess an integer number in a range, Towers of Hanoi.

Unit II: Data Types, Expressions, Statements

Python interpreter and interactive mode, debugging; values and types: int, float, boolean, string, and list; variables, expressions, statements, tuple assignment, precedence of operators, comments; Illustrative programs: exchange the values of two variables, circulate the values of n variables, distance between two points.

Unit III: Control Flow, Functions, Strings

Conditionals: Boolean values and operators, conditional (if), alternative (if-else), chained conditional (if-elif-else); Iteration: state, while, for, break, continue, pass; Fruitful functions: return values, parameters, local and global scope, function composition, recursion; Strings: string slices, immutability, string functions and methods, string module; Lists as arrays. Illustrative programs: square root, gcd, exponentiation, sum an array of numbers, linear search, binary search.

GE3151 - Problem Solving And Python Programming Syllabus Regulation 2021 Anna University

Unit IV: Lists, Tuples, Dictionaries

Lists: list operations, list slices, list methods, list loop, mutability, aliasing, cloning lists, list parameters; Tuples: tuple assignment, tuple as return value; Dictionaries: operations and methods; advanced list processing – list comprehension; Illustrative programs: simple sorting, histogram, Students marks statement, Retail bill preparation.

Unit V: Files, Modules, Packages

Files and exception: text files, reading and writing files, format operator; command line arguments, errors and exceptions, handling exceptions, modules, packages; Illustrative programs: word count, copy file, Voter’s age validation, Marks range validation (0-100).

Text Books:

Allen B. Downey, “Think Python: How to Think like a Computer Scientist”, 2nd Edition, O’Reilly Publishers, 2016.
Karl Beecher, “Computational Thinking: A Beginner’s Guide to Problem Solving and Programming”, 1st Edition, BCS Learning & Development Limited, 2017.

References:

Paul Deitel and Harvey Deitel, “Python for Programmers”, Pearson Education, 1st Edition, 2021.
G Venkatesh and Madhavan Mukund, “Computational Thinking: A Primer for Programmers and Data Scientists”, 1st Edition, Notion Press, 2021.
John V Guttag, “Introduction to Computation and Programming Using Python: With Applications to Computational Modeling and Understanding Data”, Third Edition, MIT Press 2021
Eric Matthes, “Python Crash Course, A Hands-on Project Based Introduction to Programming”, 2nd Edition, No Starch Press, 2019.
https://www.python.org/
Martin C. Brown, “Python: The Complete Reference”, 4th Edition, Mc-Graw Hill,2018.

Get details of other branches which are providing by the anna university under four year undergraduate programme connected to affiliated institutions in detailed way in this link, Anna University Regulation 2021.

[PDF] GE3151 Problem Solving and Python Programming (PSPP) Books, Lecture Notes, 2 marks with answers, Important Part B 16 Marks Questions, Question Bank & Syllabus

Download GE3151 Problem Solving and Python Programming (PSPP) Books Lecture Notes Syllabus Part-A 2 marks with answers GE3151 Problem Solving and Python Programming Important Part-B 16 marks Questions , PDF Books, Question Bank with answers Key, GE3151 Problem Solving and Python Programming Syllabus & Anna University GE3151 Problem Solving and Python Programming Question Papers Collection.

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Download link is provided for Students to download the Anna University GE3151 Problem Solving and Python Programming Syllabus Question Bank Lecture Notes Part A 2 marks with answers & Part B 16 marks Question Bank with answer , Anna University Question Paper Collection, All the materials are listed below for the students to make use of it and get good (maximum) marks with our study materials.

“GE3151 Problem Solving and Python Programming Notes, Lecture Notes, Previous Years Question Papers “

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GE3151 Problem Solving and Python Programming (PSPP) Notes Part A & Part B Important Questions with Answers

GE3151 Problem Solving and Python Programming – Study Materials – Details

	01
	Common to All Departments (Civil, CSE, ECE, EEE & Mech)
	First Year
	R2021
	GE3151 Problem Solving and Python Programming (PSPP)
	Syllabus, Question Banks, Local Authors Books, Lecture Notes, Important Part A 2 Marks Questions and Important Part B 16 Mark Questions, Previous Years Anna University Question Papers Collections.
	PDF (Free Download)

GE3151 Problem Solving and Python Programming (PSPP) “R2021 – SYLLABUS”

GE3151 PROBLEM SOLVING AND PYTHON PROGRAMMING

UNIT I COMPUTATIONAL THINKING AND PROBLEM SOLVING

UNIT II DATA TYPES, EXPRESSIONS, STATEMENTS

UNIT III CONTROL FLOW, FUNCTIONS, STRINGS

UNIT IV LISTS, TUPLES, DICTIONARIES

UNIT V FILES, MODULES, PACKAGES

TEXT BOOKS:

Allen B. Downey, “Think Python : How to Think like a Computer Scientist”, 2nd Edition, O’Reilly Publishers, 2016.
Karl Beecher, “Computational Thinking: A Beginner's Guide to Problem Solving and programming”, 1st Edition, BCS Learning & Development Limited, 2017.

REFERENCES:

Paul Deitel and Harvey Deitel, “Python for Programmers”, Pearson Education, 1st Edition,
G Venkatesh and Madhavan Mukund, “Computational Thinking: A Primer for Programmers and Data Scientists”, 1st Edition, Notion Press, 2021.
John V Guttag, "Introduction to Computation and Programming Using Python: With Applications to Computational Modeling and Understanding Data‘‘, Third Edition, MIT Press 2021
Eric Matthes, “Python Crash Course, A Hands – on Project Based Introduction to Programming”, 2nd Edition, No Starch Press, 2019.
https://www.python.org/
6. Martin C. Brown, “Python: The Complete Reference”, 4th Edition, Mc-Graw Hill,2018.

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Anna University GE3151 Problem Solving and Python Programming Books Question Banks Lecture Notes Syllabus GE3151 Problem Solving and Python Programming Part A 2 Marks with Answers Part – B 16 Marks Questions with Answers & Anna University GE3151 Problem Solving and Python Programming Question Paper Collection and Local Author Books.

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GE3151 Syllabus PROBLEM SOLVING AND PYTHON PROGRAMMING Regulation 2021 Anna University

Post author By Mr. Padeepz
Post date October 31, 2021
1 Comment on GE3151 Syllabus PROBLEM SOLVING AND PYTHON PROGRAMMING Regulation 2021 Anna University

GE3151 Syllabus PROBLEM SOLVING AND PYTHON PROGRAMMING

GE3151 Syllabus PROBLEM SOLVING AND PYTHON PROGRAMMING Regulation 2021 Anna University free download. PROBLEM SOLVING AND PYTHON PROGRAMMING Syllabus GE3151 pdf download free.

COURSE OBJECTIVES:

􀁸 To understand the basics of algorithmic problem solving. 􀁸 To learn to solve problems using Python conditionals and loops. 􀁸 To define Python functions and use function calls to solve problems. 􀁸 To use Python data structures – lists, tuples, dictionaries to represent complex data. GE3151 Syllabus PROBLEM SOLVING AND PYTHON PROGRAMMING 􀁸 To do input/output with files in Python.

UNIT I COMPUTATIONAL THINKING AND PROBLEM SOLVING

UNIT II DATA TYPES, EXPRESSIONS, STATEMENTS

UNIT III CONTROL FLOW, FUNCTIONS, STRINGS

UNIT IV LISTS, TUPLES, DICTIONARIES

UNIT V FILES, MODULES, PACKAGES

TOTAL : 45 PERIODS

COURSE OUTCOMES:

Upon completion of the course, students will be able to CO1: Develop algorithmic solutions to simple computational problems. CO2: Develop and execute simple Python programs. CO3: Write simple Python programs using conditionals and looping for solving problems. CO4: Decompose a Python program into functions. CO5: Represent compound data using Python lists, tuples, dictionaries etc. CO6: Read and write data from/to files in Python programs.

TEXT BOOKS: GE3151 Syllabus PROBLEM SOLVING AND PYTHON PROGRAMMING

1. Allen B. Downey, “Think Python: How to Think like a Computer Scientist”, 2nd Edition, O’Reilly Publishers, 2016. 2. Karl Beecher, “Computational Thinking: A Beginner's Guide to Problem Solving and programming”, 1st Edition, BCS Learning & Development Limited, 2017.

REFERENCES: GE3151 Syllabus PSPP

1. Paul Deitel and Harvey Deitel, “Python for Programmers”, Pearson Education, 1st Edition, 2021. 2. G Venkatesh and Madhavan Mukund, “Computational Thinking: A Primer for Programmers and Data Scientists”, 1st Edition, Notion Press, 2021. 3. John V Guttag, "Introduction to Computation and Programming Using Python: With Applications to Computational Modeling and Understanding Data‘‘, Third Edition, MIT Press 2021 GE3151 Syllabus PROBLEM SOLVING AND PYTHON PROGRAMMING 4. Eric Matthes, “Python Crash Course, A Hands – on Project Based Introduction to Programming”, 2nd Edition, No Starch Press, 2019. 5. https://www.python.org/ 6. Martin C. Brown, “Python: The Complete Reference”, 4th Edition, Mc-Graw Hill, 2018.

Subject name	PROBLEM SOLVING AND PYTHON PROGRAMMING
Subject Code	GE3151
Semester	1
Regulation	2021 Regulation

GE3151 Syllabus PROBLEM SOLVING AND PYTHON PROGRAMMING Click Here To Download

GE3151 Notes PROBLEM SOLVING AND PYTHON PROGRAMMING

GE3151 Important Questions PROBLEM SOLVING AND PYTHON PROGRAMMING

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1 reply on “GE3151 Syllabus PROBLEM SOLVING AND PYTHON PROGRAMMING Regulation 2021 Anna University”

Please can you give the whole book to download.

Problem solving Aspects and Python Programming

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GE3151 PSPP Notes :

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Course Status :	Ongoing
Course Type :	Core
Duration :	12 weeks
Category :
Credit Points :	4
Undergraduate
Start Date :	18 Jan 2024
End Date :	10 Apr 2024
Enrollment Ends :	29 Feb 2024
Exam Date :	26 May 2024 IST
Exam Shift: :	Shift - II

Regulation
Subject Code
Subject Name
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Why Python?

Prerequisites.

Class Logistics

Grading on a “curve”

Python example code, re-grade policy, disability resources, religious accommodations, extenuating circumstances and inclusiveness.

Welcome to CSE 160!

Computational methods permeate the sciences, engineering, and even the humanities. You need a foundational understanding of computation and practical data analysis in order to be successful in science, engineering, business, and other professions.

CSE 160, “Introduction to Data Programming”, is an introductory programming class that meets this need. You will learn to write small programs in the Python programming language to solve real-world scientific and engineering problems. This will be useful in your classes, your research, and your jobs.

In CSE 160:

You will learn computational problem-solving . After the class, if you are given a data source and a problem description, you will be able to write a complete, useful program to solve the problem.
You will learn Python , a popular and easy-to-use general-purpose programming language that includes excellent libraries for data manipulation, scientific computing, and visualization.
Assignments will use real datasets from fields such as astronomy, biology, linguistics, oceanography, open government, social networks, and more. You will see that it is easy to write programs that process data, and that doing so yields insight.
You will learn the joy and power of being able to extract understanding and insight from a mass of data.

Why another programming class?

UW offers a variety of excellent introductory programming classes. No one of them is best for all students. We provide a webpage to help you decide among them . That webpage also contains information about substituting CSE 160 for other UW requirements.

Some characteristics of CSE 160 include:

By the end of the quarter, students will be able to take a data source and a problem description and independently write a complete, useful program to solve the problem. Students will learn problem-solving and produce end-to-end solutions.
All assignments will use real scientific data, at realistic scale and complexity.
We use the Python programming language. Python is simple to learn and to use. Python has excellent libraries for data processing, scientific computing, and numerical methods. Python is widely used across the sciences, engineering, and beyond.
Students will learn enough programming concepts to permit motivated students to continue to more advanced computer science classes such as CSE 163, if desired. However, students will be independent enough not to need that for simple day-to-day data analysis and manipulation.

Many programming languages and computational tools exist to help you analyze data. These include Excel, MATLAB, R, C/C++, Java, and others. Python is a particularly good choice. It is a complete programming language. It is comparatively to learn and easy to write and read. You can get started with it right away. It comes with excellent libraries that will simplify your programs.

The Goals section described the high-level goals of the class. Its real objective is to teach you basic problem analysis and computational thinking, and to enable you to apply them in practice to extract meaning from a dataset. Doing so requires you to logically organize data; to design algorithms; to formulate them in a way that computers can execute; to test, identify problems, and find solutions; and to communicate the results.

At a lower level, here are the topics that the class teaches to help you achieve the course's goals. The schedule shows the specific order of topics during the term.

The only prerequisite for the class is high school math.

The class does not assume any previous programming experience. — in fact, if you have already taken CSE 143 or any 300-level CSE class, you are not allowed to take CSE 160.

We assume that you are familiar with basic computer usage—you are comfortable running applications, navigating the file system (say, with a tool like Windows Explorer), editing documents with a word processor or text editor, and so forth.

Any student can succeed in CSE 160. But, CSE 160 is not an easy class. To succeed requires you to work diligently, to be organized and systematic, to follow and give instructions precisely, and to ask questions when you are confused. The staff knows you can succeed, and we will help you succeed.

Class logistics: times and staff

Lectures : MWF 3:30-4:20, in CSE2 G020 Sections : Thursdays at 9:30, 10:30, 11:30, 12:30, 1:30, 2:30 and 3:30pm. See the course listing . The schedule lists readings, lecture topics and assignment due dates , with links to the materials.

Discussion Board : (aka Message Board) You may use the discussion board to ask questions — and to give help to other students. You can optionally subscribe to discussion board notifications, so that you receive email whenever a new posting is made on the discussion board.

Discussion Board etiquette : You should never post the code to solve a homework assignment (in whole or in part) on the class discussion board. This includes posting partial code in progress in order to ask what is wrong with it. Before posting your question, remember to check the discussion board (you can use the search feature) to see if it has already been asked. We encourage students to ask and answer questions on the Discussion Board.

Email etiquette : When using the staff email alias (but NOT the Discussion Board), it is always a good idea to attach the current version of your code to your message, so that the staff can better understand and reproduce your problem. In every message, always be explicit about the exact thing you did, exactly what the result was, and what you had expected to happen. (For example, cut and paste or attach the exact output, rather than just saying “something went wrong” or describing it vaguely.) This will enable us to help you more effectively.

Lecture etiquette : We encourage you to use your laptops during class for activities that help you get the most from lecture - following along with slides, typing Python code into the interpreter, taking notes. However talking and doing activities not relevant to lecture (e.g. checking emails, playing games, surfing the web) can be incredibly distracting to those around you. Please be respectful and avoid these activities during class.

Resources: books and software

The class will recommend readings from three resources. Two are freely available on the Internet, and the third is available for ~$30 or less.

Introduction to Computation and Programming Using Python (aka ICPUP) is a book about computational problem-solving that only incidentally uses the Python programming language. We will use the second edition which uses Python 3 (published August 2016, orange and blue cover). The book is also available as an e-book or paperback from a number of sellers.
Think Python . Freely available online in HTML and PDF .
The Python Tutorial , available from the Python website. This is good for explaining the nuts and bolts of how Python works.
Python Evaluation Rules
Debugging a Python program
How do I use the command-line shell?
How do I interact with files in Python?
Usage of csv.DictReader
Python style and example programs
CSE 160 Python style guide for programs
Examples of Python syntax taught in CSE 160

Readings from multiple sources are recommended for each lecture — see the schedule for details. While much of what you need to know will be discussed in lecture, most people find reading one or more resources either before or after lecture useful. before the lecture, so that we can make better use of lecture time, answer your questions about the readings, and discuss more advanced topics. There is a brief reading quiz due before lecture (see each quiz for its exact due time), as a Catalyst survey that should take you only a few minutes to complete, if you have done the reading. We expect you to complete nearly all of them and to get a score above 50% on most of the quizzes. After the quiz closes, you can view the quiz again to see your score and the correct answers. -->

The assigned readings are a great place to get started, but you will also need to use other materials to master Python. We also encourage you to use the many Python resources that are available on the Web. Start with the official Python documentation , whose most useful components include a beginner's guide , a tutorial , a list of all the functions built into Python , and searchable online documentation .

Software : Please see the CSE 160 computing resources webpage for information about installing Python on your own computer.

Tools : Philip Guo's Python Tutor lets you execute a program line by line, and it draws the variables and data structures that the program creates during execution.

After CSE 160 : If you wish to learn more beyond what CSE 160 teaches you, see the self-study suggestions .

Assignments and Grading

Assignments are available from the schedule and also, redundantly, on a separate homework webpage . Assignment submission forms are linked to on their respective specification documents.

Your course grade will be determined approximately as follows (weights may be slightly modified):

Assignments 60%
Participation 10%

You will complete approximately six programming assignments . There are often some written questions on each assignment as well as a survey that must be filled out as well.

We urge you in the strongest possible terms to get started on your assignments early. This approach will take you much less time overall than if you try to do all the work at once at the last minute. An efficient approach is to start work, then take a break when needed. This lets your subconscious continue to work on the problem, or enables you to return to it with a fresh perspective and renewed energy. Furthermore, you will be able to ask for and receive help.

HW4-part1 and HW5-part1 will each count as 4% of your Assignments grade.
HW1, HW2, HW3, HW6 will each count as 11% of your Assignments grade.
HW4-part2 and HW5-part2 will each count as 13% of your Assignments grade.
HW7(your final project) part0, part1 and part3 will each count as 2% of your Assignments grade.
HW7-part2 will count as 16% of your Assignments grade.

The exam grade will be determined by a midterm and a final exam. The final will count a bit more than the midterm exam. Our midterm will be held Wednesday, Feb 2nd and our final exam will be held Thursday, Mar 17th. More details about exam formats will be announced later.

Your participation grade includes check-ins (on-line questions and programming exercises), homework surveys, as well as other course activities. In-person attendance at lectures or section will not be required for the participation grade.

If you find an error in our grading, please bring it to our attention within one week of that item being returned.

Grading for this class is not curved in the sense that the average is set at (say) 3.0 and half of the class must receive a grade lower than that. If everyone does well and shows mastery of the material, everyone can receive an A. If no one does well (this is unlikely), then everyone can receive a C. Furthermore, your grade is not affected by someone else dropping the class — whether that person was doing better or worse than you.

Grading for this class is curved in the sense that we do not have a pre-defined mapping from homework and exam scores to a final GPA. There is no pre-determined score (e.g., 90% of all possible points) that earns a 4.0 or a 3.5 or a 2.0 or any other grade. To determine the final grade, we will ask questions like “Did this student master the material?”, and the English descriptions in the Sample UW Grading Guidelines .

Assignments are due on different days of the week, generally at 11:59pm. Due dates will be listed on each assignment and shown on the schedule .

Each student is permitted 5 late days to use during the quarter. Each late day permits you to submit an assignment up to 24 hours late. Each late day is atomic; for example, you cannot use 8 hours of a single late day on each of three assignments. Note that some assignments may have multiple parts. Each part of the assignment should be viewed as its own assignment in terms of late days. For example, submitting HW4-part1 1 day late and HW4-part2 1 day late will consume two late days.

You may wish to reserve some late days in case of unexpected emergencies (please let us know about medical emergencies such as those involving hospitalization). If you have used up your late days, a penalty of 10% off per 24-hours late will be assessed. Regardless of the number of late days you have remaining, assignments will not be accepted more than two days after the original due date . An exception is made for weekends, which count as a single late day. That is, if an assignment is due at 11:59pm on Friday, submitting before Sunday at 11:59pm counts as using only ONE late day (submitting by 11:59pm on Monday would count as using TWO late days).

Important: If you have already submitted work for an assignment, but plan on resubmitting an improved version AFTER the deadline, please send email to [email protected] so we know you will be submitting work late. This way we won't grade your earlier submission and will know to wait for your late submission. You do not need to do this every time you submit late, just if you already submitted something that we might assume was your final submission. (We don't want to grade your homework more than once!)

Academic Honesty

Integrity is a crucial part of your character and is essential for a successful career. We expect you to demonstrate integrity in CSE 160 and elsewhere. In particular, your assignments must represent your own work and understanding. Academic misconduct such as plagiarism is grounds for failing the class and will be dealt with by a University committee.

The following guidelines apply unless an assignment specifically states otherwise. If you have any questions about acceptable behavior, please ask the course staff. We will be happy to answer your questions!

You are encouraged to talk to your classmates about problem solution ideas , and you may reuse those ideas , but you may not examine nor reuse any other student's code - this includes code from students who have taken this course or a similar one in previous quarters . You are not allowed to copy code from any source — other students, acquaintances, the Web, etc. (Copying is forbidden via cut-and-paste, via dictation or transcription, via viewing and memorizing, etc.) Your solution may utilize Python libraries that are available that we have discussed in lecture. You are encouraged to use books, the Internet, your friends, etc. to get solution ideas , but you may not copy/transcribe/transliterate code: get the idea, close the other resource, and then (after enough time that the idea is in your long-term, not short-term, memory - e.g. watch a silly TV show for at least 30 minutes) generate the code yourself based on your own understanding.

You may sometimes find it useful to do a web search to find snippets of Python code that performs some particular operation , and paste it into your own programs. (Remember: It is NEVER acceptable to examine or re-use code from another student, including students who have taken this course or a similar one in previous quarters.) This can be an acceptable short-term strategy if it helps you get past a particular roadblock. However, you must later go back, remove the code you did not write yourself, and write the replacement on your own, from scratch. Recall that the class policy is that you must write everything that you turn in. Violating this is academic dishonesty (cheating), which can lead to a variety of negative consequences for you, including failing the class and further disciplinary action.

It is your responsibility to understand everything that you turn in. We reserve the right to ask you to explain any part of your homework assignment. If you are not able to explain what it means and why you chose it, that is presumed evidence of copying/cheating.

Later, when you are writing your own programs after you complete CSE 160, it's fine to copy others' code if the license permits such use. (Copying one or two lines is usually acceptable regardless of the license.) However, in your future career, please remember two things:

It is your ethical duty to properly cite the source of any code that you did not write yourself. Give credit where credit is due.
You should still understand the code that you copied. Otherwise, if and when the code does not work (for example, maybe the original author made an assumption that is not true in your program, or worse yet, it has a bug!), you will lose more time debugging than you saved by copying.

The key idea in all this is that we want you to understand. Sometimes you can achieve that by examining and understanding other people's code. But you can never achieve that by copying alone.

Since our programming assignments and exams will be graded via Gradescope, you should make use of the regrade-request system within Gradescope to request regrades on these. Re-grades will typically remain open for a week (or slightly more) after work has been returned via Gradescope.
For anything submitted outside of Gradescope (e.g. CodingBat exercises), please:
Along with a reference (link) to the original version of the assignment you wish to have re-graded, you must also include a written summary describing why the work should be looked at again.
Email your request to the cse160-staff@cs list.
Re-grade requests should be submitted within a week of when the assignment was returned.

Note that when an assignment or test is re-graded, the entire work will be re-graded. This means that while it is possible to regain some points, it is also possible to lose points.

The Disability Resources for Students (DRS) is a unit within the Division of Student Life and is dedicated to ensuring access and inclusion for all students with disabilities on the Seattle campus. They offer a wide range of services for students with disabilities that are individually designed and remove the need to reveal sensitive medical information to the course staff. If you have a medical need for extensions of assignment deadlines, these will only be granted through official documentation from DRS. Browse to this link to start the process as soon as possible to avoid delays.

You can refer to the university policies regarding Disability Accommodations for more information.

We recognize that our students come from varied backgrounds and can have widely-varying circumstances. If you have any unforeseen or extenuating circumstance that arise during the course, please do not hesitate to contact the instructor in office hours, via email, or private discussion board post to discuss your situation. The sooner we are made aware, the more easily these situations can be resolved. Extenuating circumstances include work-school balance, familial responsibilities, military duties, unexpected travel, or anything else beyond your control that may negatively impact your performance in the class.

Additionally, if at any point you are made to feel uncomfortable, disrespected, or excluded by a staff member or fellow student, please report the incident so that we may address the issue and maintain a supportive and inclusive learning environment. Should you feel uncomfortable bringing up an issue with a staff member directly, you may consider sending feedback or contacting the Office of the Ombud .

All of the information in this document is subject to change throughout the quarter. The course staff will announce any substantive changes.

Browse Course Material

Course info, instructors.

Dr. Ana Bell
Prof. Eric Grimson
Prof. John Guttag

Departments

Electrical Engineering and Computer Science

As Taught In

Algorithms and Data Structures
Programming Languages

Learning Resource Types

Introduction to computer science and programming in python, course meeting times.

Lectures: 2 sessions / week, 1 hour / session

Recitations: 1 sessions / week, 1 hour / session

Course Information

6.0001 Introduction to Computer Science and Programming in Python is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students, regardless of their major, feel justifiably confident of their ability to write small programs that allow them to accomplish useful goals. The class will use the Python 3.5 programming language.

This is a half-semester course. Students who successfully complete 6.0001 may continue into 6.0002 Introduction to Computational Thinking and Data Science , which is taught in the second half of the semester.

Provide an understanding of the role computation can play in solving problems.
Help students, including those who do not plan to major in Computer Science and Electrical Engineering, feel confident of their ability to write small programs that allow them to accomplish useful goals.
Position students so that they can compete for research projects and excel in subjects with programming components.

Lecture and Recitation Attendance

A significant portion of the material for this course will presented only in lecture, so students are expected to regularly attend lectures.

Recitations give students a chance to ask questions about the lecture material or the problem set for the given week. Sometimes, new material may be covered in recitation. Recitation attendance is encouraged but not required.

Problem Sets and Quizzes

Each problem set will involve programming in Python. There will be 6 problem sets in the course. There will be two quizzes. All quizzes will be closed-book, though you will be allowed to bring one page of notes to the first quiz and two pages of notes to the second quiz. Pages must be letter-sized, double-sided, either handwritten or typed.

Grading Policy

Grades will be roughly computed as follows:

ACTIVITIES	PERCENTAGES
Problem sets	30%
Completion of mandatory finger exercises	10%
Midterm Quiz	20%
Final Quiz	40%

Problem sets will be graded out of 10 points. Submissions that do not run will receive at most 20% of the points. Please contact your Teaching Assistant if you have a problem understanding your problem set grade.

Note: Quizzes and finger exercises are not available on OpenCourseWare.

Extension and Dropping Problem Sets Policy

We do not grant any extensions. Instead, we offer late days and the option of rolling at most 2 problem set grades into the final quiz score.

At the beginning of the term, students are given two late days that they can use on problem sets. Starting with Problem Set 1, additional late days can be accumulated for each assignment, one late day for each day the assignment is turned in ahead of the deadline. Up to three late days may be accumulated in this fashion in this course, i.e you can only have a maximum of 3 late days at any point in time. Late days are discrete (a student cannot use half a late day). The staff will keep track of late days and feedback for each problem set will include the number of late days the student has remaining. Any additional late work beyond these late days will not be accepted. To avoid surprises, we suggest that after you submit your problem set, you double check to make sure the submission was uploaded correctly.

Rolling Over Problem Sets

Before the final quiz, we will send out an announcement in which you can choose at most 2 problem sets that you can drop. If dropped, the percent that the problem sets are worth will be rolled into the final quiz score. We strongly urge you to see the late days and dropping the problem sets as backup in case of an emergency. Your best strategy is to do the problem sets early before work starts to pile up.

SES #	TOPICS	ASSIGNMENTS
1	What is computation?	Pset 0 released
2	Branching and Iteration	Pset 1 released
3	String Manipulation, Guess and Check, Approximations, Bisection	Pset 0 due
4	Decomposition, Abstractions, Functions	Pset 2 released
5	Tuples, Lists, Aliasing, Mutability, Cloning	Pset 1 due
6	Recursion, Dictionaries	Pset 3 released
7	Testing, Debugging, Exceptions, Assertions	Pset 2 due; Quiz 1
8	Object Oriented Programming
9	Python Classes and Inheritance	Pset 3 due; Pset 4 released
10	Understanding Program Efficiency, Part 1	Pset 4 due; Pset 5 released
11	Understanding Program Efficiency, Part 2
12	Searching and Sorting	Pset 5 due; Final Quiz

You are leaving MIT OpenCourseWare

Problem Solving and Python Programming - GE3151, GE8151

Important questions and answers, question paper download, online study material, lecturing notes, assignment, reference, wiki.

Exam Question Papers

Question bank, problem solving and python programming, unit i: computational thinking and problem solving, unit ii: data types, expressions, statements, unit iii: control flow, functions, strings, unit iv: lists, tuples, dictionaries, unit i : algorithmic problem solving, unit ii : data expressions statements, unit iii : control flow functions, unit iv : lists tuples dictionaries, unit v : files modules packages.

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[PDF] GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual)

Download GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) from the below link. The students & the lectures can download the Anna University GE3171 Problem Solving and Python Programming Lab Manual for their Laboratory examination in the first semester examination of GE3171 subject. The students to make use of it and score good (maximum) marks in the exams with our study materials.

“GE3171 Problem Solving and Python Programming Lab Manual”

“GE3171 Problem Solving and Python Programming Laboratory Manual PDF”

“GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual)”

“Download GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual)”

You all must have this kind of questions in your mind. The below article will solve this puzzle of yours. Just take a look and download the study materials.

GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual)

1.1 GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) Syllabus
1.2 Download Link
1.3 GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) Syllabus
1.4 GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual)
1.5 Anna University Useful Links
1.6 Other Useful Links
1.7 GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) – FAQ

GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) – Details

	01
	Common for All Engineering Departments
	First Year (I Year)
	2021
	GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual)
	Laboratory Manual
	PDF (Free Download)

GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) Syllabus

Identification and solving of simple real life or scientific or technical problems, and developing flow charts for the same. (Electricity Billing, Retail shop billing, Sin series, weight of a motorbike, Weight of a steel bar, compute Electrical Current in Three Phase AC Circuit, etc.)
Python programming using simple statements and expressions (exchange the values of two variables, circulate the values of n variables, distance between two points).
Scientific problems using Conditionals and Iterative loops. (Number series, Number Patterns, pyramid pattern)
Implementing real-time/technical applications using Lists, Tuples. (Items present in a library/Components of a car/ Materials required for construction of a building –operations of list & tuples)
Implementing real-time/technical applications using Sets, Dictionaries. (Language, components of an automobile, Elements of a civil structure, etc.- operations of Sets & Dictionaries)
Implementing programs using Functions. (Factorial, largest number in a list, area of shape)
Implementing programs using Strings. (reverse, palindrome, character count, replacing characters)
Implementing programs using written modules and Python Standard Libraries (pandas, numpy. Matplotlib, scipy)
Implementing real-time/technical applications using File handling. (copy from one file to another, word count, longest word)
Implementing real-time/technical applications using Exception handling. (divide by zero error, voter’s age validity, student mark range validation)
Exploring Pygame tool.
Developing a game activity using Pygame like bouncing ball, car race etc.

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Regulation 2021 GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) Syllabus – DOWNLOAD
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GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) – FAQ

What is the Full Form of the Subject Code GE3171?

The Full Form of Subject Code GE3171 is Problem Solving and Python Programming Laboratory Manual .

How to Download GE3171 Lab Manual?

The students can download the GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) on the EasyEngineering website for preparing their upcoming First Semester examination.

Where to Download GE3171 Lab Manual PDF?

On the EasyEngineering GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) page, the students can download the Lab Manual PDF , which contains list of Experiment/ Exercises.

In which regulation semester exam GE3171 subject is studied?

The GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) subject is studied by the Anna University Students of First Year in their First Semester Examination of 2021 Regulation .

How to download Anna University GE3171 syllabus?

The GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) Syllabus is directly downloaded from the Anna University Regulation 2021 Syllabus page on the EasyEngineering.

How to check Anna University GE3171 Internal Marks?

The GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) Anna University Internal marks can be check by the students from the official portal of Anna University ( coe1.annauniv.edu ) . The steps to check the Anna University Internal marks are clearly explained in the EasyEngineering Anna University Internal Mark checking page.

How to check Anna University GE3171 exam results?

The GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) Anna University semester examination results can be check by the students from the official result checking pages/portals (i.e., aucoe.annauniv.edu or coe1.annauniv.edu ). Also, In the EasyEngineering website the Results checking page are available to check the Anna University current semester examination results quickly.

How to check Anna University GE3171 Grace marks details?

In the Easyengineering GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) page contains the grace mark details to notify the students to know about the grace marks provided by Anna University for the invalid or out of portions/syllabus questions asked in the current First Semester GE3171 exam.

Which Engineering department is studying the GE3171 as one subject?

The GE3171 Problem Solving and Python Programming Laboratory Manual (Lab Manual) subject is studied by the Anna University First Year students of Common For all departments such us Civil Engineering (CE), Mechanical Engineering (ME), Electrical and Electronics Engineering (EEE), Electronics and Communication Engineering (ECE), Electronics and Instrumentation Engineering (EIE), Computer Science Engineering (CSE), Aeronautical Engineering, Automobile Engineering & Other departments as one subject in their First Semester examination.

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Problem Solving and Python Programming (GE8151) Notes, Question Papers & Syllabus

APR/MAY 2023 EXAMS

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PART A B & C
NOTES
PART A B & C
NOTES
QN’ PAPERS
SYLLABUS

Engineering Graphics (GE3251) [EG] Notes, Question Papers & Syllabus

Basic electrical, electronics and instrumentation engineering (be3252) [beeie] notes, question papers & syllabus, electric circuit analysis (ee3251) [eca] notes, question papers & syllabus.

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CS106B Course Home and Syllabus

Summer Quarter 2024. Lecture MTWTh 1:30 - 2:45 PM in Skilling Auditorium.

🗺️ Your Week 1 Task Map

Section begins this week, LaIR hours start Thursday, and we have a bunch of start-up task deadlines:

Tue 5:00 PM - Sign up for section!

Fri 11:59 PM - Syllabus Quiz
Fri 11:59 PM - Assignment #0
Fri 11:59 PM - Lecture Quiz Series #1

See Julián's Week #1 post on ed for more.

Course Overview and Welcome

Hi there 👋, and welcome to CS106B: Programming Abstractions! This is the second course in our introductory programming sequence. The prerequisite, CS106A, establishes a solid foundation in programming methodology and problem-solving in Python. With that under your belt, CS106B will acquaint you with the C++ programming language and introduce advanced programming techniques such as recursion, algorithm analysis, and data abstraction, explore classic data structures and algorithms, and give you practice applying these tools to solving complex problems. .

We're excited to share this great material with you and have a superb team of section leaders that will support you through the challenges to come. We hope you will find the time worth your investment and that you enjoy your growing mastery of the art of programming!

Teaching Team

We have an incredible group of undergraduate section leaders (SLs) who lead weekly sections and help students 1-on-1 in LaIR hours. Read more about the teaching team and office/LaIR hours .

Course Topics

Overview of main topics.

Our planned curriculum will cover the following topics in this approximate order:

Data abstraction, classic ADTs
Recursion and backtracking
Classes and object-oriented programming
Pointers and dynamic memory
Linked data structures
Advanced algorithms

Learning Goals

After completing CS106B, we hope you will have achieved the following learning goals:

I am excited to use programming to solve real-world problems I encounter outside class.
I recognize and understand common abstractions in computer science.
I can identify programmatic concepts present in everyday technologies because I understand how computers process and organize information.
I can break down complex problems into smaller subproblems by applying my algorithmic reasoning and recursive problem-solving skills.
I can evaluate design tradeoffs when creating data structures and algorithms or utilizing them to implement technological solutions.

We’ll also be giving you tools to tackle the following questions (note that these don’t have single right or wrong answers!):

What is possible with technology and code? What isn’t possible?
How can I use programming to solve problems that I otherwise would not be able to?
What makes for a “good” algorithm or data structure? Why?
Which problems should I solve with algorithms and data structures? What does a responsible programmer do when using data about real people?

Prerequisites

The prerequisite for CS106B is completion of CS106A and readiness to move on to advanced programming topics. A comparable introductory programming course or experience (including high school AP courses) is often a reasonable substitute for Stanford’s CS106A. If you are unsure if this course is the right for you, read more about course placement .

Course Structure

Lecture meets MTWTh 1:30 PM - 2:45 PM in Skilling Auditorium. Lecture recordings will be posted on Canvas for future review, but we ask that you treat regular lecture attendance as a professional obligation as an enrollee of this course. All students are expected to attend lectures in person if at all feasible (i.e., unless you are sick or an SCPD remote student), in order to fully participate in class discussions and other synchronous activities, as well as to stay on top of course material and get the most out of . We understand that this isn't possible for every student every time, so if you are unable to attend we ask that you at least watch the video of class before the next class, so you are up to speed on all course topics and important announcements. Read more about lectures .

Note about recording consent: Video cameras are located in the back of the lecture room to capture the instructor presentation. These recordings might be reused in other Stanford courses, viewed by other Stanford students, faculty, or staff, or used for other education and research purposes. While the cameras are positioned with the intention of recording only the instructor, occasionally a part of your image or voice might be incidentally captured. If you have questions, please contact a member of the teaching team.

Each students is assigned to a weekly small group discussion section, led by an undergraduate section leader. Your section leader is your mentor, grader, and personal connection to the greater CS106B course staff.

Sections begin the first week of classes, and attendance and participation are mandatory for all students. Your section leader will evaluate your section participation; this contributes to your course grade.

Assignments

There will be regular assignments, about one per week. An assignment may include written problems, hands-on exercises with the tools, coding tasks and/or a larger complete program. Assignments are to be completed individually.

Programs are graded on "functionality" (is the program's behavior correct?) and "style" (is the code well-written and designed cleanly?). We use a bucket grading scale to focus attention on the qualitative rather than quantitative feedback. Read more about assignments, grading, and late policy .

We have mid-quarter and end-quarter exams. The mid-quarter is a check-in to assess your understanding of core topics covered in the first half of the course and help you chart a path forward. The final is a comprehensive assessment of your mastery of the course learning goals.

Mark these dates in your calendar now!

Midterm: Friday, July 19, 1:30 - 3:30 PM
Final: Friday, August 16, 3:30 - 6:30 PM

Course Grades

Final grades for the course will be determined using the following weights:

38% Programming assignments
20% Mid-quarter exam
35% End-quarter final exam
5% Section participation
2% Quiz 0 on canvas

In order to receive a passing grade in the course, you must earn a passing grade on the programming assignments as well as (collectively) the exams (i.e., failing an exam will not disqualify you from passing the course, as long as your average across both exams is a passing grade). So, someone who has a passing exam average but a failing average on the programming assignments, or vice versa, will not receive a passing grade in the course.

If you are an undergraduate, you must enroll in CS106B for 5 units (this is by department and university policy, no exceptions). If you are a graduate student, you may enroll in CS106B for 3 or 4 units to reduce your units for administrative reasons. Taking the course for reduced units has no change on the course workload.

Incompletes

The university “I” grade (“incomplete”) is sometimes appropriate for circumstances of significant personal or family emergency disruption that occur late in the quarter and prevent a student from finishing course requirements on schedule. In order to be eligible for an Incomplete, University policy stipulates that a student must have completed a “substantial” part of the course work in “satisfactory” fashion. There must also be extenuating circumstances that warrant an extension of time beyond the end of the quarter to complete the remaining work. Approval for an incomplete is at the instructors’ discretion. Incompletes are not be considered for reasons such as poor performance in the course or over-commitment. Withdrawal from the course is more appropriate in those cases.

Time Is of the Essence

We require timely notification if any circumstances arise that impact your ability to meet the requirements, deadlines, and expectations of the course in a way that our late assignment submission policy does not already accommodate – generally in advance of any impacted deadlines (including exam dates).

Generally speaking, we ask that you treat this course as you would any professional obligation. Think of project deadlines and exam dates the same way you would think of big project deadlines at work: if it became clear you weren't going to be able to meet such a deadline, or if you weren't going to have a presentation ready in time for a big quarterly staff meeting, your manager would want to know about that well in advance.

As a student taking a Stanford course, you agree to abide by the Stanford Honor Code, and we expect you to read over and follow our specific CS106B Honor Code policy . The work you submit for grading must be your own original, independent effort and must not be based on, guided by, or jointly developed with the work of others.

The CS department employs powerful automated plagiarism detection tools that compare assignment submissions with other submissions from the current and previous quarters, as well as related online resources. The tools also analyze your intermediate work, and we will run the tools on every assignment you submit.

The vast majority of you are here to learn and will do honest work for an honest grade. We celebrate and honor your commitment. Because it’s important that all cases of academic dishonesty are identified for the sake of those playing by the rules, we will refer all cases of concern to the Office of Community Standards.

Regret Clause

When people are under pressure, they sometimes do things they later regret. My impression from talking with students over the years is that this is often the case with students who violate the Honor Code in my classes: they’re good people who make bad decisions they almost immediately regret. Accordingly, if you end up violating the Honor Code while working on an assignment in this course, you can mitigate the consequences by informing me of your infraction within 72 hours after the late deadline for the assignment. In response, the only penalty you will face for that infraction is a zero on the assignment. I will not lower your grade further as a result of the infraction, and I will not refer the matter to the Office of Community Standards.

To take advantage of this "regret clause," you must fill out the retraction form we will make available after each assignment deadline. We do not anticipate allowing retractions outside the 72-hour window for each assignment, and we will not do a last call for retractions at the end of the quarter.

This policy is modeled after the regret clause in Harvard's CS50 class .

Course Resources

Roberts, Eric. Programming Abstractions in C++ . ISBN 978-0133454840.

You can find different options to access the textbook here . Recommended readings for each lecture will be posted on our lecture schedule.

The official CS106 programming environment is Qt Creator , which is an editor bundled with C++ compiler and libraries. The software runs on Windows, Mac, and Linux and is free for personal/student use. The Qt Installation Guide has instructions for installing the tools onto your computer.

Getting Help

We want to enable everyone to succeed in this course and offer different paths to help.

The instructors and Head TA will hold weekly office hours. The section leaders staff LaIR helper hours. The CS106B Ed Discussion forum allows public Q&A and discussion with your peers. Here is the Quick Start Guide to using Ed .

Accommodations

Students who need an academic accommodation based on the impact of a disability should initiate a request with the Office of Accessible Education. Professional staff will evaluate the request with required documentation, recommend reasonable accommodations, and prepare an Accommodation Letter dated in the current quarter. Students should contact the OAE as soon as possible since timely notice is needed to coordinate accommodations. The OAE has contact information on their web page: http://oae.stanford.edu . Once you obtain your OAE letter, please send it to the head TA .

Course Tools

The central place for CS106B resources is the course website right here at https://cs106b.stanford.edu . The website is your go-to for course materials (lectures, assignments, sections, exams) and course policies and information.

We also make use use these additional tools:

Canvas to publish lecture videos and lecture quizzes.
Ed Discussion forum for online community, Q&A, and posted announcements.
Paperless , our custom site for submitting assignments and viewing grading feedback.
LaIR , our custom tool for mananging the queue in helper hours.
Gradescope , for viewing graded exams.

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CBSE Class 11 Syllabus

CBSE Class 11 Informatics Practices Syllabus 2024-25: Download The PDF For Free Here!

Cbse class 11 informatics practices syllabus 2024-25: this article will provide the latest insights on the cbse class 11 syllabus. to check the revised informatics practices syllabus, download the free pdf from the direct link. .

CBSE Class 11 Informatics Practices Syllabus 2024-25: The syllabus of Informatics Practices for class 11 is designed in such a way that it helps the learners to identify the components of the computer system, creating Python programs with the help of different types of data available, lists and dictionaries, understanding the database concepts and the theory for Relational Database Management Systems.

The curriculum provided on the official website of CBSE academic all the necessary details like the course structure and the distribution of marks.

Keep reading the article to learn about the syllabus.

Learning Outcomes

Identify the components of the computer system.
Create Python programs using different data types, lists and dictionaries.
Understand database concepts and Relational Database Management Systems.
Retrieve and manipulate data in RDBMS using Structured Query Language
Identify the Emerging trends in the fields of Information Technology.

CBSE Class 11 Informatics Practices Syllabus 2024-25

CBSE Class 11 Informatics Practices Unit Wise Syllabus

Unit 1: Introduction to Computer System

Introduction to computer and computing: evolution of computing devices, components of a computer system and their interconnections, Input/output devices.

Computer Memory: Units of memory, types of memory – primary and secondary, data deletion, its recovery and related security concerns.

Software: purpose and types – system and application software, generic and specific purpose software.

Unit 2: Introduction to Python

Basics of Python programming, execution modes: - interactive and script mode, the structure of a program, indentation, identifiers, keywords, constants, variables, types of operator, precedence of operators, data types, mutable and immutable data types, statements, expression evaluation. comments, input and output statements, data type conversion, and debugging.

Control Statements: if-else, if-elif-else, while loop, for loop

Lists: list operations - creating, initializing, traversing and manipulating lists, list methods and built-in functions – len(), list(), append(), insert(), count(), index(), remove(), pop(), reverse(), sort(), min(), max(), sum()

Dictionary: the concept of key-value pair, creating, initializing, traversing, updating and deleting elements, dictionary methods and built-in functions – dict(), len(), keys(), values(), items(), update(), del, clear()

Unit 3: Database Concepts and the Structured Query Language

Database Concepts: Introduction to database concepts and its need, Database Management System.

Relational data model: Concept of domain, tuple, relation, candidate key, primary key, alternate key

Advantages of using Structured Query Language, Data Definition Language, Data Query Language and Data Manipulation Language, Introduction to MySQL, creating a database using MySQL, Data Types

Data Definition: CREATE DATABASE, CREATE TABLE, DROP, ALTER

Data Query: SELECT, FROM, WHERE with relational operators, BETWEEN, logical operators, IS NULL, IS NOT NULL

Data Manipulation: INSERT, DELETE, UPDATE

Unit 4: Introduction to the Emerging Trends

CBSE Class 11 Informatics Practice Practical Marks Distribution

Suggested Practical List

To find the average and grade for given marks.
To find the sale price of an item with a given cost and discount (%).
To calculate the perimeter/circumference and area of shapes such as triangles, rectangles, squares and circles.
To calculate Simple and Compound interest.
To calculate profit-loss for a given Cost and Sell Price.
To calculate EMI for Amount, Period and Interest.
To calculate tax - GST / Income Tax.
To find the largest and smallest numbers in a list.
To find the third largest/smallest number in a list.
To find the sum of squares of the first 100 natural numbers.
To print the first ‘n’ multiples of a given number.
To count the number of vowels in user entered string.
To print the words starting with an alphabet in a user-entered string.
To print several occurrences of a given alphabet in each string.
Create a dictionary to store the names of states and their capitals.
Create a dictionary of students to store names and marks obtained in 5 subjects.
To print the highest and lowest values in the dictionary.
To create a database
To create a student table with the student ID, class, section, gender, name, dob, and marks as attributes where the student ID is the primary key.
To insert the details of at least 10 students in the above table.
To display the entire content of the table.
To display Rno, Name and Marks of those students who are scoring marks more than 50.
To display the Rno, Name, and DOB of those students who are born between ‘2005- 01-01’ and ‘2005-12-31’.

Suggested material: NCERT Informatics Practices - Textbook for class - XI

Now, that the students have the syllabus with them, they can easily download it in PDF from the link below.

CHECK: CBSE Class 11 Informatics Practises Syllabus 2024-25

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[PDF] GE3151 Problem Solving and Python Programming (PSPP) Books
Python
SOLUTION: Ge8151 problem solving python programming
Problem Solving & Python Programming for BE Anna University
GE3151 Problem Solving and Python Programming syllabus
GE8151

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GE3151
To define Python functions and use function calls to solve problems. To use Python data structures - lists, tuples, dictionaries to represent complex data. To do input/output with files in Python. GE3151 - Problem Solving And Python Programming Syllabus. Unit I: Computational Thinking And Problem Solving
[PDF] GE3151 Problem Solving and Python Programming (PSPP) Books
Download link is provided for Students to download the Anna University GE3151 Problem Solving and Python Programming Syllabus Question Bank Lecture Notes Part A 2 marks with answers & Part B 16 marks Question Bank with answer, Anna University Question Paper Collection, All the materials are listed below for the students to make use of it and get good (maximum) marks with our study materials.
GE3151 problem solving and python programming
1. GE3151 PROBLEM SOLVING AND PYTHON PROGRAMMING 3 0 0 3 COURSE OBJECTIVES: To understand the basics of algorithmic problem solving. To learn to solve problems using Python conditionals and loops. To define Python functions and use function calls to solve problems. To use Python data structures - lists, tuples, dictionaries to represent complex ...
GE3151 Syllabus PROBLEM SOLVING AND PYTHON PROGRAMMING ...
Upon completion of the course, students will be able to. CO1: Develop algorithmic solutions to simple computational problems. CO2: Develop and execute simple Python programs. CO3: Write simple Python programs using conditionals and looping for solving problems. CO4: Decompose a Python program into functions.
GE3151 PSPP Syllabus Problem Solving and Python Programming
OBJECTIVES: To understand the basics of algorithmic problem solving. To learn to solve problems using Python conditionals and loops. To define Python functions and use function calls to solve problems. To use Python data structures - lists, tuples, dictionaries to represent complex data. To do input/output with files in Python.
PDF Notes of Lesson Ge3151- Problem Solving and Python Programming
sub function add() =a+b Step 4: Printc Step 5: Return2.NOTATIONS OF AN ALGORITHMAlgorithm can be expressed in many different notations, including Natur. l Language, Pseudo code, flowcharts and programming. languages. Natural language tends to be verbose and ambiguous. Pseudocode an.
CIS 1051:Introduction to Problem Solving and Programming in Python
DESCRIPTION. CIS 1051 introduces students to computers, computer programming, and problem solving using programs written in the Python language. . Topics covered include the general characteristics of computers; techniques of problem solving and algorithm specifications; and the implementation, debugging, and testing of computer programs.
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GE3151 Problem Solving and Python Programming Syllabus - Free download as PDF File (.pdf), Text File (.txt) or read online for free. GE3151 Problem solving and Python pogramming - SYLLABUS ( Anna University - 2021 Regulations - I SEM - Common for all branches)
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Python ProgrammingAnna University, Chennai Anna University was established on 4th S. ptember 1978 as a unitary type of University. It offers higher education in engineering, technology and allied sciences relevant to t. urrent and projected needs of the society. Madras Institute of Technology (MIT) is a campus of Anna University offers higher ...
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GE3151 & GE3171 Syllabus - Free download as PDF File (.pdf), Text File (.txt) or read online for free. Syllabus of GE3151 PROBLEM SOLVING AND PYTHON PROGRAMMING GE3171 PROBLEM SOLVING AND PYTHON PROGRAMMING LABORATORY
GE3151 Problem Solving and Python Programming syllabus
COURSE OBJECTIVES: To understand the basics of algorithmic problem solving. To learn to solve problems using Python conditionals and loops. To define Python functions and use function calls to solve problems. To use Python data structures - lists, tuples, dictionaries to represent complex data. To do input/output with files in Python.
Problem solving Aspects and Python Programming
This course is designed for use by freshmen students taking their first course in programming. It deals with the techniques needed to practice computational thinking, the art of using computers to solve problems and the ways the computers can be used to solve problems. The Second part covers Python Programming.
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GE3151 PSPP Notes : We are providing the GE3151 Problem Solving and Python Programming Lecture Notes, and Hand Written Notes Collections PDF below for your examination success. use our Materials to score good marks in the examination. Best of Luck. Regulation. 2021.
Problem Solving and Programming with Python
gure 1.6 Solving the Tower of Hanoi problem. We will be solving this using a spare pole. In our case, A is the source pole, C is th. destination pole, and B is the spare pole. To transfer all the three rings from A to C, we will first shift the upper two rings (n-1 rings) from the source pole to the spare pol.
GE8151
HS8151 - Communicative English - Regulation 2017 Syllabus. NEXT POST GE8291 - Environmental Science and Engineering - Regulation 2017 Syllabus. Anna University Problem Solving and Python Programming - GE8151 syllabus for all Unit 1,2,3,4 and 5 B.E/B.Tech - UG Degree Programme.
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There are 4 modules in this course. This course provides an introduction to programming and the Python language. Students are introduced to core programming concepts like data structures, conditionals, loops, variables, and functions. This course includes an overview of the various tools available for writing and running Python, and gets ...
Syllabus
You will learn to write small programs in the Python programming language to solve real-world scientific and engineering problems. This will be useful in your classes, your research, and your jobs. Goals. In CSE 160: You will learn computational problem-solving. After the class, if you are given a data source and a problem description, you will ...
Syllabus
Course Meeting Times. Lectures: 2 sessions / week, 1 hour / session. Recitations: 1 sessions / week, 1 hour / session. Course Information. 6.0001 Introduction to Computer Science and Programming in Python is intended for students with little or no programming experience. It aims to provide students with an understanding of the role computation can play in solving problems and to help students ...
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To understand the basics of algorithmic problem solving. To learn to solve problems using Python conditionals and loops. To define Python functions and use function calls to solve problems. To use Python data structures - lists, tuples, dictionaries to represent complex data. To do input/output with files in Python. UNIT
Problem Solving and Python Programming
GE8151 Problem Solving and Python Programming - Anna University 2017 Regulation Syllabus Download GE8151 Problem Solving and Python Programming - Question Bank Download. Download Android App for Anna University - Book Download Android App for Anna University - PDF.
GE3151 Syllabus Problem Solving AND Python Programming
GE3151 Syllabus PROBLEM SOLVING AND PYTHON PROGRAMMING COURSE OBJECTIVES: 􀁸 To understand the basics of algorithmic problem solving. 􀁸 To learn to solve problems using Python conditionals and loops. 􀁸 To define Python functions and use function calls to solve problems. 􀁸 To use Python data structures - lists, tuples, dictionaries to represent complex data.
[PDF] GE3171 Problem Solving and Python Programming ...
The students & the lectures can download the Anna University GE3171 Problem Solving and Python Programming Lab Manual for their Laboratory examination in the first semester examination of GE3171 subject. The students to make use of it and score good (maximum) marks in the exams with our study materials. "GE3171 Problem Solving and Python ...
Problem Solving and Python Programming (GE8151) Notes ...
SYLLABUS. CLICK HERE. PREVIOUS POST Anna University Special Case - Nov/Dec 2022 Examinations. NEXT POST Anna University Internal Marks - UG/PG Examinations. Anna University MCQ Q&A, Notes, Question Bank, Question Paper for Problem Solving and Python Programming (GE8151) semester exams.
CS106B Course Home and Syllabus
Fri 11:59 PM - Syllabus Quiz; Fri 11:59 ... and welcome to CS106B: Programming Abstractions! This is the second course in our introductory programming sequence. The prerequisite, CS106A, establishes a solid foundation in programming methodology and problem-solving in Python. With that under your belt, CS106B will acquaint you with the C++ ...
PDF CSE 1321L: Programming and Problem Solving I Lab Assignment 5
3) Problem solving Overview: We will be making a basic video game using PyGame. While the result of this project should be fun, the real goal is to give you the opportunity to apply everything you've learned about programming up to this point. There are many fields of software development, but the
CBSE Class 11 Informatics Practices Syllabus 2024-2025: Download Class
Class 11 Informatics Practices Syllabus 2024-2025: Get here detailed CBSE Class 11th Informatics Practices Syllabus chapter-wise, marking scheme, weightage, paper pattern and Download PDF.

GE3151 – Problem Solving And Python Programming Syllabus Regulation 2021 Anna University

[PDF] GE3151 Problem Solving and Python Programming (PSPP) Books, Lecture Notes, 2 marks with answers, Important Part B 16 Marks Questions, Question Bank & Syllabus

GE3151 Problem Solving and Python Programming (PSPP) Notes Part A & Part B Important Questions with Answers

GE3151 Problem Solving and Python Programming Lecture Notes

GE3151 Problem Solving and Python Programming Unit wise 2 marks Question with Answers

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