Here are 15 FREE courses you don’t want to miss:
1. Introduction to Computer Science
About this course:
This is CS50x , Harvard University’s introduction to the intellectual enterprises of computer science and the art of programming for majors and non-majors alike, with or without prior programming experience. An entry-level course taught by David J. Malan, CS50x teaches students how to think algorithmically and solve problems efficiently. Topics include abstraction, algorithms, data structures, encapsulation, resource management, security, software engineering, and web development. Languages include C, Python, SQL, and JavaScript plus CSS and HTML. Problem sets inspired by real-world domains of biology, cryptography, finance, forensics, and gaming. The on-campus version of CS50x , CS50, is Harvard’s largest course.
Students who earn a satisfactory score on 9 problem sets (i.e., programming assignments) and a final project are eligible for a certificate. This is a self-paced course–you may take CS50x on your own schedule.
HarvardX requires individuals who enroll in its courses on edX to abide by the terms of the edX honor code. HarvardX will take appropriate corrective action in response to violations of the edX honor code, which may include dismissal from the HarvardX course; revocation of any certificates received for the HarvardX course; or other remedies as circumstances warrant. No refunds will be issued in the case of corrective action for such violations. Enrollees who are taking HarvardX courses as part of another program will also be governed by the academic policies of those programs.
HarvardX pursues the science of learning. By registering as an online learner in an HX course, you will also participate in research about learning. Read our research statement to learn more.
Harvard University and HarvardX are committed to maintaining a safe and healthy educational and work environment in which no member of the community is excluded from participation in, denied the benefits of, or subjected to discrimination or harassment in our program. All members of the HarvardX community are expected to abide by Harvard policies on nondiscrimination, including sexual harassment, and the edX Terms of Service. If you have any questions or concerns, please contact [email protected] and/or report your experience through the edX contact form.
2. Introduction to Game Development
About this course:
In a quest to understand how video games themselves are implemented, you’ll explore the design of such childhood games as:
- Super Mario Bros.
- Pong
- Flappy Bird
- Breakout
- Match 3
- Legend of Zelda
- Angry Birds
- Pokémon
- 3D Helicopter Game
- Dreadhalls
- Portal
3. Introduction to Programming with Scratch
About this course:
An introduction to programming using Scratch, a visual programming language via which aspiring programmers can write code by dragging and dropping graphical blocks (that resemble puzzle pieces) instead of typing out text. Used at the start of Harvard College’s introductory course in computer science, CS50, Scratch was designed at MIT’s Media Lab, empowering students with no prior programming experience to design their own animations, games, interactive art, and stories. Using Scratch, this course introduces students to fundamentals of programming, found not only in Scratch itself but in traditional text-based languages (like Java and Python) as well. Topics include: functions, which are instructions that perform tasks; return values, which are results that functions provide; conditions, via which programs can decide whether or not to perform some action; loops, via which programs can take action again and again; variables, via which programs can remember information; and more. Ultimately, this course prepares students for subsequent courses in programming.
Scratch is developed by the Lifelong Kindergarten Group at the MIT Media Lab. See scratch.mit.edu.
4. Web Programming with Python and JavaScript
About this course:
Topics include database design, scalability, security, and user experience. Through hands-on projects, you’ll learn to write and use APIs, create interactive UIs, and leverage cloud services like GitHub and Heroku. By course’s end, you’ll emerge with knowledge and experience in principles, languages, and tools that empower you to design and deploy applications on the Internet.
5. Computer Science for Business Professionals
About this course:
This is CS50’s introduction to computer science for business professionals, designed for managers, product managers, founders, and decision-makers more generally. Whereas CS50 itself takes a bottom-up approach, emphasizing mastery of low-level concepts and implementation details thereof, this course takes a top-down approach, emphasizing mastery of high-level concepts and design decisions related thereto. Through lectures on computational thinking, programming languages, internet technologies, web development, technology stacks, and cloud computing, this course empowers you to make technological decisions even if not a technologist yourself. You’ll emerge from this course with first-hand appreciation of how it all works and all the more confident in the factors that should guide your decision-making.
6. CS50 for Lawyers
About this course:
This course is a variant of HarvardUniversity’s introduction to computer science, CS50, designed especially for lawyers (and law students). Whereas CS50 itself takes a bottom-up approach, emphasizing mastery of low-level concepts and implementation details thereof, this course takes a top-down approach, emphasizing mastery of high-level concepts and design decisions related thereto. Ultimately, it equips students with a deeper understanding of the legal implications of technological decisions made by clients.
Through a mix of technical instruction and discussion of case studies, this course empowers students to be informed contributors to technology-driven conversations. In addition, it prepares students to formulate technology-informed legal arguments and opinions. Along the way, it equips students with hands-on experience with Python and SQL, languages via which they can mine data for answers themselves.
Topics include algorithms, cloud computing, databases, networking, privacy, programming, scalability, security, and more, with a particular emphasis on understanding how the work developers do and the technological solutions they employ may impact clients. Students emerge from this course with first-hand appreciation of how it all works and all the more confident in the factors that should guide their decision-making.
Keywords:law firm, computer programming, programming skills, computer programmers, patent attorney, legal practice, legal services, legal education, patent law
7. Introduction to Artificial Intelligence with Python
About this course:
AI is transforming how we live, work, and play. By enabling new technologies like self-driving cars and recommendation systems or improving old ones like medical diagnostics and search engines, the demand for expertise in AI and machine learning is growing rapidly. This course will enable you to take the first step toward solving important real-world problems and future-proofing your career.
CS50’s Introduction to Artificial Intelligence with Python explores the concepts and algorithms at the foundation of modern artificial intelligence, diving into the ideas that give rise to technologies like game-playing engines, handwriting recognition, and machine translation. Through hands-on projects, students gain exposure to the theory behind graph search algorithms, classification, optimization, reinforcement learning, and other topics in artificial intelligence and machine learning as they incorporate them into their own Python programs. By course’s end, students emerge with experience in libraries for machine learning as well as knowledge of artificial intelligence principles that enable them to design intelligent systems of their own.
Enroll now to gain expertise in one of the fastest-growing domains of computer science from the creators of one of the most popular computer science courses ever, CS50. You’ll learn the theoretical frameworks that enable these new technologies while gaining practical experience in how to apply these powerful techniques in your work.
8. Introduction to Programming with Python
About this course:
An introduction to programming using a language called Python. Learn how to read and write code as well as how to test and “debug” it. Designed for students with or without prior programming experience who’d like to learn Python specifically. Learn about functions, arguments, and return values (oh my!); variables and types; conditionals and Boolean expressions; and loops. Learn how to handle exceptions, find and fix bugs, and write unit tests; use third-party libraries; validate and extract data with regular expressions; model real-world entities with classes, objects, methods, and properties; and read and write files. Hands-on opportunities for lots of practice. Exercises inspired by real-world programming problems. No software required except for a web browser, or you can write code on your own PC or Mac.
Whereas CS50x itself focuses on computer science more generally as well as programming with C, Python, SQL, and JavaScript, this course, aka CS50P, is entirely focused on programming with Python. You can take CS50P before CS50x, during CS50x, or after CS50x. But for an introduction to computer science itself, you should still take CS50x!
9. Data Science: Machine Learning
About this course:
Perhaps the most popular data science methodologies come from machine learning. What distinguishes machine learning from other computer guided decision processes is that it builds prediction algorithms using data. Some of the most popular products that use machine learning include the handwriting readers implemented by the postal service, speech recognition, movie recommendation systems, and spam detectors.
In this course,part ofourProfessional Certificate Program in Data Science, you will learn popular machine learning algorithms, principal component analysis, and regularization by building a movie recommendation system.
You will learn about training data, and how to use a set of data to discover potentially predictive relationships. As you build the movie recommendation system, you will learn how to train algorithms using training data so you can predict the outcome for future datasets. You will also learn about overtraining and techniques to avoid it such as cross-validation. All of these skills are fundamental to machine learning.
10. Data Science: Productivity Tools
About this course:
A typical data analysis project may involve several parts, each including several data files and different scripts with code. Keeping all this organized can be challenging.
Part of our Professional Certificate Program in Data Science, this course explains how to use Unix/Linux as a tool for managing files and directories on your computer and how to keep the file system organized. You will be introduced to the version control systems git, a powerful tool for keeping track of changes in your scripts and reports. We also introduce you to GitHub and demonstrate how you can use this service to keep your work in a repository that facilitates collaborations.
Finally, you will learn to write reports in R markdown which permits you to incorporate text and code into a document. We’ll put it all together using the powerful integrated desktop environment RStudio.
11. Understanding Technology
About this course:
This is CS50’s introduction to technology for students who don’t (yet) consider themselves computer persons. Designed for those who work with technology every day but don’t necessarily understand how it all works underneath the hood or how to solve problems when something goes wrong, this course fills in the gaps, empowering you to use and troubleshoot technology more effectively. Through lectures on hardware, the Internet, multimedia, security, programming, and web development, this course equips you for today’s technology and prepares you for tomorrow’s as well.
12. Mobile App Development with React Native
About this course:
This course picks up where CS50 leaves off, transitioning from web development to mobile app development with React Native.
The course introduces you to modern JavaScript (including ES6 and ES7) as well as to JSX, a JavaScript extension. Through hands-on projects, you’ll gain experience with React and its paradigms, app architecture, and user interfaces. The course culminates in a final project for which you’ll implement an app entirely of your own design.
13. Introduction to Data Science with Python
About this course:
Every single minute, computers across the world collect millions of gigabytes of data. What can you do to make sense of this mountain of data? How do data scientists use this data for the applications that power our modern world?
Data science is an ever-evolving field, using algorithms and scientific methods to parse complex data sets. Data scientists use a range of programming languages, such as Python and R, to harness and analyze data. This course focuses on using Python in data science. By the end of the course, you’ll have a fundamental understanding of machine learning models and basic concepts around Machine Learning (ML) and Artificial Intelligence (AI).
Using Python, learners will study regression models (Linear, Multilinear, and Polynomial) and classification models (kNN, Logistic), utilizing popular libraries such as sklearn, Pandas, matplotlib, and numPy. The course will cover key concepts of machine learning such as: picking the right complexity, preventing overfitting, regularization, assessing uncertainty, weighing trade-offs, and model evaluation. Participation in this course will build your confidence in using Python, preparing you for more advanced study in Machine Learning (ML) and Artificial Intelligence (AI), and advancement in your career.
Learners must have a minimum baseline of programming knowledge (preferably in Python) and statistics in order to be successful in this course. Python prerequisites can be met with an introductory Python course offered through CS50’s Introduction to Programming with Python, and statistics prerequisites can be met via Fat Chance or with Stat110 offered through HarvardX.
14. Artificial Intelligence in Business: Creating Value with Machine Learning.
About this course:
Learn how to manage and apply artificial intelligence in the global business world. Develop an understanding of when to pursue new technologies and how they fit into your business strategy.
15. Fundamentals of TinyML
About this course:
What do you know about TinyML? Tiny Machine Learning (TinyML) is one of the fastest-growing areas of Deep Learning and is rapidly becoming more accessible. This course provides a foundation for you to understand this emerging field.
TinyML is at the intersection of embedded Machine Learning (ML) applications, algorithms, hardware, and software. TinyML differs from mainstream machine learning (e.g., server and cloud) in that it requires not only software expertise, but also embedded-hardware expertise.
The first course in the TinyML Certificate series, Fundamentals of TinyML will focus on the basics of machine learning, deep learning, and embedded devices and systems, such as smartphones and other tiny devices. Throughout the course, you will learn data science techniques for collecting data and develop an understanding of learning algorithms to train basic machine learning models. At the end of this course, you will be able to understand the “language” behind TinyML and be ready to dive into the application of TinyML in future courses.
Following Fundamentals of TinyML, the other courses in the TinyML Professional Certificate program will allow you to see the code behind widely-used Tiny ML applications—such as tiny devices and smartphones—and deploy code to your own physical TinyML device. Fundamentals of TinyML provides an introduction to TinyML and is not a prerequisite for Applications of TinyML or Deploying TinyML for those with sufficient machine learning and embedded systems experience.
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