Tree Recursion

Function (computer programming)

Scoping

Algorithmic Complexity

2048

Python

Object-Oriented Programming (OOP)

Higher-order function (HOF)

Algorithms

Best Coding Practices

Programming Paradigms

List Mutation

Social Implications

Abstraction (computer science)

List (abstract data type)

Mutability

Recursion (computer science)

Fractals

Python Data Structures

Number Representation

Concurrency

CS 10: The Beauty and Joy of Computing UC Berkeley Summer 2022 A gentle, thorough introduction to computer science, starting with block-based language Snap! and transitioning to Python. The course covers fundamental programming concepts and encourages application in various fields.
Level: Beginner friendly. Welcome to CS10: The Beauty and Joy of Computing! We’re really excited to have you on board with us this Summer for a gentle but thorough introduction to computer science. Our course will start out in the blocks-based language Snap!, but will transition into Python once you have learned some fundamentals of programming. By the end of the class, we hope you walk away with a deeper understanding of the ideas that have come to define computer science, the ability to build your own programs, and the confidence to apply these skills in whichever field you choose to pursue.   

CS 10: The Beauty and Joy of Computing

Computer Programming

Sequences

Tree (data structure)

Generators

Inheritance (object-oriented programming)

Linked list

Scheme

Interpreters

Aggregation

Single View Metrology

Computer Science

Environments

Functional Abstraction

Data Abstraction

Iterators

Object (computer science)

Efficiency

Data Examples

Calculator

Tables

Control

Higher-Order Environments

Containers

Gates & Circuits

Ethics and Bias in Computer Science

Scheme Lists

String (computer science)

CS 61A: Structure and Interpretation of Computer Programs UC Berkeley Fall 2022 A course that emphasizes software abstraction, equipping students with the skills to manage program complexity. Students will primarily use Python, with additional exposure to Scheme and SQL. The CS 61 series is an introduction to computer science, with particular emphasis on software and on machines from a programmer's point of view.

1. CS 61A concentrates on the idea of abstraction, allowing the programmer to think in terms appropriate to the problem rather than in low-level operations dictated by the computer hardware.
1. CS 61B deals with the more advanced engineering aspects of software, such as constructing and analyzing large programs.
1. CS 61C focuses on machines and how they execute programs.

In CS 61A, we are interested in teaching you about programming, not about how to use one particular programming language. We consider a series of techniques for managing program complexity, such as functional programming and object-oriented programming.

CS 61A primarily uses the Python 3 programming language. Python is a popular language in both industry and academia. It is also particularly well-suited to the task of exploring the topics taught in this course. It is an open-source language developed by a large volunteer community that prides itself on the diversity of its contributors.

Mastery of a particular programming language is a very useful side effect of CS 61A. However, our goal is not to dictate what language you use in your future endeavors. Instead, our hope is that once you have learned the concepts involved in programming, you will find that picking up a new programming language is but a few days' work. In fact, you will be asked to learn at least two other languages, Scheme and SQL, during the course.

A complete list of lecture topics, readings, and assignments appears in the [lecture schedule](https://cs61a.org/).  Math 1A is listed as a corequisite for CS 61A. That is, it may be taken concurrently. Math 10A or Math 16A are also fine. It is possible to take CS 61A without knowing or learning calculus. Knowledge of calculus concepts will never be required to complete any assignments. However, taking calculus is a great way to brush up on the arithmetic and algebra that appear regularly in CS 61A.

There is no formal programming-related prerequisite for CS 61A, but taking the course without any prior programming experience is typically very challenging. Students who take the course without prior programming experience typically must work substantially harder to master the material and tend to receive lower final grades in the course. Most CS 61A students have had significant prior programming experience. A typical background includes at least one course equivalent to CS 10 or a score of 3 or above on the AP Computer Science A exam.

If you find it challenging to complete all of the required coursework in the first three weeks, you are **strongly recommended** to take another course first. You'll likely have a better experience taking 61A later. Taking CS 61A one semester later is unlikely to affect your degree progress or otherwise put you behind, but continuing to struggle in CS 61A despite this recommendation can lead to difficult academic circumstances that can affect your future opportunities. It's better to finish CS 61A with strong mastery of the course material, even if that means delaying by a semester, than to rush through it. The online textbook for the course is [Composing Programs](http://composingprograms.com/), which was created specifically for this course, based on the classic textbook [Structure and Interpretation of Computer Programs](https://mitpress.mit.edu/sites/default/files/sicp/index.html). Readings for each lecture appear in the course schedule. We recommend that you complete the readings before attending lecture.

Lots of additional study materials including past exams appear on the [Resources](https://cs61a.org/resources/) page.

CS 61A: Structure and Interpretation of Computer Programs

Loops

For Loop

Environment Diagrams

Dictionaries

Mutable Data

Databases

Lambda

Abstract Data Type (ADT)

Exception handling

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

Recursive tree

Tree Recursion

3 courses cover this concept

CS 10: The Beauty and Joy of Computing

CS 61A: Structure and Interpretation of Computer Programs

CS 88: Computational Structures in Data Science