Dictionaries

Control flow

Expressions

List (abstract data type)

Images

Computer memory

Search algorithm

Decomposition

Python Control Flow

Graphics

List of Lists

Computer file

Data Science

Internet

Python Variables

Function (computer programming)

Graphical Animation

String (computer science)

Nested Structures

Class (computer programming)

Function Variables

CS 106A: Programming Methodologies Stanford University Spring 2023 This is an introductory course offering step-by-step instruction on key programming concepts with Python, including control flow, decomposition, data science, and more. Students are guided through exercises to learn by doing. ### How Does This Class Work?

- Start the very beginning
- Careful to go step by step, little exercises every day
- Like swimming, you can't just read about it
- Learn by doing
- "reps" - Nick's favorite word
- Technology to practice ideas right away
- In just a couple weeks .. amazed at what you can do
- Partly because computers are powerful
- Partly because coding is easier than you think  No prior programming experience required. There is one required text for this class, entitled Karel the Robot Learns Python. It's a short interactive tutorial that introduces the major concepts in programming in the context of an extremely simple robot world. This text is available for free on the class website. In addition to this text, we will also have reference material on Python available via the class webpage.

CS 106A: Programming Methodologies

Computer Programming

Abstraction (computer science)

Loops

For Loop

Environment Diagrams

Recursion (computer science)

Object-Oriented Programming (OOP)

Mutable Data

Linked list

Tree (data structure)

Generators

Databases

Higher-order function (HOF)

Lambda

Abstract Data Type (ADT)

Tree Recursion

Inheritance (object-oriented programming)

Efficiency

Exception handling

Iterators

Programming Paradigms

CS 88: Computational Structures in Data Science UC Berkeley Fall 2022 This course provides an introduction to computer science with an emphasis on functional programming, data abstraction, object-oriented programming, and program complexity. The course teaches foundational programming concepts primarily in Python. CS 88 is a "connector" for Data 8 that is designed for students who would like a more complete introduction to Computer Science. We will cover a variety of topics such as functional programming, data abstraction, object-oriented programming, and program complexity. This course will be taught primarily in Python. However, we are interested in teaching you foundational programming ideas, not just how to use one particular programming language. Once you have learned the essence of programming and the concepts that appear in various forms in programming languages, you will be able to pick up other languages and other programming concepts rapidly.

The material for this course has significant overlap with CS 61A. We do not cover the interpretation section of CS61A. If you are certain that you want to major or minor in Computer Science, CS 61A is the right introductory course. You can take CS 61A for credit after having taken CS 88. However, you cannot take CS 88 for credit after having taken CS 61A. Data 8 and CS 88 together satisfy the knowledge prerequisite for CS 61B.  It is recommended, but not required, that you are currently enrolled in or have taken Data 8. There is no formal programming-related prerequisite for CS 88. You do not need to be familiar with any particular programming language. The online textbook for the course is [Composing Programs](http://composingprograms.com/), which was created specifically for CS61A but is also the best basis for this course. Readings for each lecture appear in the course schedule. We will be jumping around a little due to the data-centric orientation of the course. You should complete the readings before attending lecture.

In addition, the course website and Piazza will contain additional links to guides, handouts, and practice materials available for the course.

CS 88: Computational Structures in Data Science

Data Structures and Algorithms

Dictionaries

2 courses cover this concept

CS 106A: Programming Methodologies

CS 88: Computational Structures in Data Science