Whether you're a budding programmer or simply curious about the fascinating realms of computer science, free online courses can help you grow in this field with no money you spend — just effort and commitment.
In this compilation of the best accessible computer science courses in 2023, we shed light on the high-quality educational online resources that cater to learners of all levels. So, if you're just about learning to program or want to refresh your existing knowledge, read on and make your choice!
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Part 1 includes the following modules: Course Introduction, Union-Find, Analysis of Algorithms, Stacks and Queues, Elementary Sorts, Mergesort, Quicksort, Priority Queues, Elementary Symbol Tables, Balanced Search Trees, Geometric Application of BSTs, Hash Tables, Symbol Table Applications.
Part 2 includes the following modules: Introduction, Undirected Graphs, Directed Graphs, Minimum Spanning Trees, Shortest Paths, Maximum Flow and Minimum Cut, Radix Sorts, Tries, Substring Search, Regular Expressions, Data Compression, Reductions, Linear Programming, Intractability.
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Introduction to Computer Science by Harvard University
"Introduction to Computer Science" is an entry-level course Harvard University offers. It introduces both majors and non-majors to computer science and programming. The course covers algorithms, data structures, software engineering, web development, and more. The course is suitable for people with or without prior programming experience. It's taught by David J. Malan, Doug Lloyd, and Brian Yu, who teach students to think algorithmically and solve problems efficiently. The course is self-paced, and students who complete nine problem sets and a final project can earn a certificate. The course lasts 12 weeks (6–18 hours per week).
What you'll learn:
- Basics of computer science and programming
- How to solve programming problems
- Concepts like algorithms, data structures, abstraction, encapsulation, security, resource management, software engineering, and web development
- Get familiarity with such programming languages as C, Python, SQL, JavaScript, CSS, and HTML
- How to collaborate with like-minded students
- How to create and present a final programming project
Introduction to Computer Science and Programming Specialization by University of London
Like the previous course, "Introduction to Computer Science and Programming Specialization" is a good choice for newbies still hesitating about whether programming is their thing. The course will help you learn fundamental computing principles and how to navigate computational tools. It'll also give you a solid understanding of various computer operations that apply across different software and systems. The course has a flexible schedule and lasts two months (granted, you devote 10 hours per week per learning). After completing the course, you'll earn a career certificate from the University of London. The course is divided into such topics:- Introduction to Computer Programming (21 hours)
- How Computers Work (8 hours)
- Mathematics for Computer Science (35 hours)

What you'll learn:
- Basics of computer science
- How different computer systems work
- How to use Javascript to create interactive programs in the browser
- How to convert between number base
- How to work with modular arithmetic, sequences, and series, as well as plot graphs
AI For Everyone by DeepLearning.AI
If you think AI is only for engineers, you can't be further from the truth. And specialists from Stanford University prove this with their course. The "Introduction to Artificial Intelligence" is mainly non-technical and suitable for students of all levels, even with no programming background. The course is taught by Andrew Ng and consists of 4 modules:- What is AI (9 videos, 1 quiz)
- Building AI projects (8 videos, 1 quiz)
- Building AI in your company (10 videos, 1 quiz)
- AI and society (8 videos, 1 reading, 1 quiz)

What you'll learn:
- Common AI terminology
- Ethical and societal discussions surrounding AI and how to navigate them
- What AI can and can't do
- How to apply AI to problems in your organization
- How to build machine learning and data science projects
- How to work with an AI team
Algorithms Part 1 and Part 2 by Princeton University
In this course, you'll delve into the fundamental concepts every programmer should master – algorithms and data structures. The emphasis is on practical applications and analyzing Java implementations for scientific performance. Part I covers elementary data structures, sorting, and searching algorithms, while Part II focuses on the graph and string-processing algorithms. Kevin Wayne and Robert Sedgewick taught the course. It's entirely free, offering all its features without any cost. However, please note that it does not provide a certificate upon completion. The course is self-paced, and Part 1 lasts approximately 54 hours (3 weeks at 18 hours a week), whereas Part 2 lasts 62 hours (3 weeks at 20 hours a week). Previous experience is optional.
Machine Learning Specialization by Stanford University and Deeplearning.AI
You'll like this comprehensive course if you're willing to explore the essentials of machine learning and discover the transformative world of AI. Led by renowned AI expert Andrew Ng, this beginner-friendly program covers the foundational principles of machine learning and can help you create your first real-world AI application. The course is split into three sections:- Supervised Machine Learning: Regression and Classification
- Advanced Learning Algorithms
- Unsupervised Learning, Recommenders, Reinforcement Learning

What you'll learn:
- How to build ML models with NumPy & scikit-learn
- How to apply the best practices for ML development and use unsupervised learning techniques for unsupervised learning
- How to build and train a neural network with TensorFlow to perform multi-class classification
- How to build and use decision trees
- How to create recommender systems with a collaborative filtering approach
- How to build a deep reinforcement learning model
Introduction to Operating Systems by Georgia Tech
"Introduction to Operating Systems" is an advanced graduate-level course designed to introduce you to the fascinating world of operating systems. Throughout this program, you'll delve into the fundamental abstractions, mechanisms, and implementations that form the backbone of modern operating systems. The course centers around concurrent programming, threading, synchronization, and inter-process communication, offering invaluable insights into how different processes interact. The course consists of 4 modules:- Introduction
- Process and Thread Management
- Resource Management and Communication
- Distributed Systems

What you'll learn:
- Understand the rationale behind the current design and implementation decisions in modern OS's
- Get theoretical knowledge regarding OS's principles and implementation
- Gain knowledge via experimenting and evaluating various OS aspects in a practical manner
Introduction to Cybersecurity by Cisco
In our modern interconnected world, cyber-attacks leave nobody untouched. This course may be the perfect solution if you're concerned about safeguarding your or your company's sensitive data. It explores the latest cyber trends and threats, providing relevant and practical knowledge that resonates with nearly every situation. With a focus on protecting your privacy in the digital realm, this course sheds light on the challenges that companies, governmental entities, educational institutions, and financial services face today. No prerequisites are required, making this learning course accessible to all. The course lasts 15 hours and offers a mixed learning type: instructor-led and online self-paced. After completing the course, you'll get a badge.
What you'll learn:
- What cybersecurity is and what potential impact it may have on you
- The most common threats, attacks, risks, and vulnerabilities
- Understand how businesses protect their systems
- Find more about the latest job trends and why cybersecurity increasingly becomes popular
Deep Learning Specialization by Deeplearning.ai
This foundational program is aimed at intermediate-level students who want to polish their deep learning and AI skills. It'll help you better understand the capabilities and challenges of deep learning and prepare you for participating in the development of AI technology. The program offers students to build and train several neural network architectures, analyze data, implement optimization techniques, and use algorithms for advanced tasks. The Deep Learning Specialization program consists of 5 courses:- Neural Networks and Deep Learning (24 hours)
- Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization (23 hours)
- Structuring Machine Learning Projects (6 hours)
- Convolutional Neural Networks (35 hours)
- Sequence Models (34 hours)

What you'll learn:
- How to build and train deep neural networks
- How to implement vectorized neural networks
- How to apply DL to your applications
- How to train and develop test sets and analyze bias/variance for building DL applications
- How to implement a neural network in TensorFlow
- How to use best strategies for reducing errors in ML systems
- How to build a Convolutional Neural Network
- How to build and train Recurrent Neural Networks and its variables (GRUs, LSTMs), and many more
Cloud Computing Specialization by the University of Illinois
Those interested in cloud computing may like the Cloud Computing Specialization created by the University of Illinois. It covers numerous aspects of cloud computing systems, starting with core distributed systems concepts and ending with cloud apps and networking. The program is for intermediate-level students who want to enhance their knowledge in software-defined networking, big data, and distributed computing. The program includes 6-course series:- Cloud Computing Concepts, Part 1 (23 hours)
- Cloud Computing Concepts: Part 2 (19 hours)
- Cloud Computing Applications, Part 1: Cloud Systems and Infrastructure (15 hours)
- Cloud Computing Applications, Part 2: Big Data and Applications in the Cloud (19 hours)
- Cloud Networking (22 hours)
- Cloud Computing Project (21 hours)

What you'll learn:
- Cloud computing and its main technologies
- What is software-defined networking
- How distributed computing works
- Basics of big data
Java Programming: Solving Problems with Software by Duke University
Ultimately, we'd like to present the program to help you enhance your knowledge of Java. The "Java Programming: Solving Problems with Software" course is created to improve your problem-solving skills. Also, you'll recall how to design algorithms and develop/debug programs. The course consists of 5 modules:- Introduction to the course
- Fundamental Java Syntax and Semantics
- String in Java
- CSV Files and Basic Statistic in Java
- MiniProject: Baby Names

What you'll learn:
- How to edit, compile, and run a Java app
- How to use conditionals and loops
- How to use Java API documentation
- How to debug a Java program using the scientific method
- How to develop a set of test cases
- How to create a class with multiple methods
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