Top The Best AI Courses

The best AI courses include general fundamentals in AI as well as topics such as (but are not limited to) machine learning procedures and deep learning procedures, as well as individual courses such as natural language processing and data mining. All right now, let’s consider the first of the best AI courses!

Artificial Intelligence Nanodegree

Details

• Rating: 4.8
• Pricing: 3 months for $1017
• Level:  Beginner–Intermediate
• Best For:  Lite boot camp, Career
• Course Link: Enroll

Who should take this course?

Whoever wants to get acquainted with many AI approaches from leading experts.

What you will gain from this course

The subject of this course is less extensive than Norvig’s textbook but covers similar ground, providing an introduction to the main AI methods. It is not generative AI and it’s the tools you learn, and there is no machine learning here—you could consider it a basic course.

Since I bought Norvig’s text for autonomous learning, I appreciated including this course to have more background knowledge and receive grading via quizzes and projects.

Every module in the course is also preceded by projects that review what has been taught in the class to the learners. These include the construction of a sudoku solver, a forward-planning agent, an adversarial game-playing agent, and a part of a speech tagging model. 

These projects will consolidate your knowledge in the areas where you have worked and enhance your portfolio.

Who’s teaching?

Peter Norvig is co-author of Artificial Intelligence: A Modern Approach, which is a book that is commonly used in many University’s AI programs.

His experience includes:

• Led Google’s search algorithm group
• Leading NASA’s Computational Sciences Division
• Created an online Stanford AI course which attracted more than 160000 registrants whereby worked together with other tutors
• Norvig is the author of the practical text, but at the same time, the author managed to explain all the topics from the field of AI in detail, providing students with both a strong theoretical background and intuition.

Syllabus

• Foundations of AI: Current state and future trends of AI, including concepts of agents, environment, and state. Constraint satisfaction methods and the search are discussed: uninformed and informed.
• Solving Complex Problems: Constraint propagation, backtracking search, and solving Sudoku and other puzzles using the Conda package manager of Python.
• Search and Planning: Presentation of the methods of classical graph search, automated planning using logic, as well as other classical optimization techniques in the realm of A*
• , including hill climbing and simulated annealing.
• Adversarial and Probabilistic Models: Minimax and alpha-beta search algorithms as well as pattern finding methodologies such as Bayes Nets and Hidden Markov Models.
• Practical Applications: Every part of the syllabus has projects like a Sudoku solver, a forward-planning agent for automation, and an adversarial game-playing agent that showcases how AI methods and approaches function in practice.

In summary, this course provides a good background in artificial intelligence methods. The content of the course resembles many introductory AI classes given at universities and is delivered by two of the industry’s leading experts.

The professional certificate in pc technological know-how for synthetic Intelligence

• Best For: Introductory Computer Science Education
• Best For: Computer Science beginners, challenging problems
• Course Link:  Enroll

Who should take this course?

The specific target of this website would be AI learners who wish to have a better groundwork on computer science.

Here is what you will expect to gain from this course

This is edX, a five-month professional certificate course that emulates Harvard’s in-person CS50 course. It is one of the easiest computer science courses you will find online why?

The characteristic feature of this program is the abundance of individual and difficult problems. The first course allows you to build programs that sometimes force you to question your knowledge of coding, algorithms, and data structures that are core to software engineering, specifically for AI.

The next course deepens the subject by presenting basic concepts of Artificial Intelligence, and all modules call for creating several AI programs.

The initiatives you build can have an AI do things like:

• Solve games such as Tictactoe and Minesweeper.
• Build crossword puzzles.
• Recognize traffic signs in photographs (for automated vehicles, for example).
• Distinguish the subjects from the objects or even the objects from the actions or maybe the different types of the objects (NLP).
• Identify what a mask word might be in a sentence (language models).
• Some of the programming languages that are included in sections of this course might be difficult for a student who has never seen code to follow. But if you have a good start in CS, it might be more suitable and time-saving to go to the second course.

Last but not least, the copyright of this remarkable program belongs to the instructors and communities. Supported by very high video production value, easily one of the best teachers I have had in an online class. 

And because of this program, the instructors and teaching assistants have developed a very large and very active community of other CS and AI learners.

Who’s teaching?

The first instructor you’ll meet is David J. Malan – a computer scientist and a professor at Harvard University’s School of Engineering and Applied Sciences. He is most famous because of one course that has garnered a lot of demand – CS50. 

Besides Harvard, he also served as the Chief Information Officer at Mindset Media where he designed infrastructures to make hundreds of millions of HTTP requests per day for the generation of large data sets.

In the second course, mathematics teacher Brian Yu will tell you more about Artificial Intelligence. Yu is a software developer and educator who also teaches at Harvard and makes educational content in computer science on Spanning Tree, his YouTube channel.

Syllabus

Course 1: A discipline that investigates issues concerning computers belongs to an area of study referred to as Introduction to Computer Science.

• Introduction to Computer Science: Fundamental concepts.
• Programming with C: It comprises data type, operators if and loops, function, variables, debugging, and arrays, as well as command-line arguments.
• Algorithms: that introduce topics I haven’t found in other sources, including linear search, binary search, bubble sort, selection sort, recursion, and merge sort.
• Memory: Explains hexadecimal, pointers, custom types, dynamic memory, call stacks, and file pointers.
• Data Structures: Introduces singly-linked lists and their performance for a set; describes hash tables and tries.
• Programming with Python: Python Programming: An overview.
• Using SQL with Python: A case of using SQL databases in Python software systems.
• Web Programming: Micro topics include; Internet, Internet Protocol, Transmission Control Protocol, Hypertext Transfer Protocol, Hypertext markup language, Cascading style sheets, JavaScript, Document object model, Flask web servers, and Ajax.

His experience includes:

• Led Google’s search algorithm group
• Leading NASA’s Computational Sciences Division
• Created an online Stanford AI course which attracted more than 160000 registrants whereby worked together with other tutors
• Norvig is the author of the practical text, but at the same time, the author managed to explain all the topics from the field of AI in detail, providing students with both a strong theoretical background and intuition.

 AI for beginner | Free SkillUp Course

This is an online free course in AI, which is crucial for those who wish to make students have their first encounter with artificial intelligence. 

PGP in data science includes a brief review of AI concepts, application areas, and the impact of Artificial Intelligence on Business Industries, forming a foundation for further elaboration.

 A Comprehensive Guide to Deep Learning | SkillUp

This Simplilearn course covers knowledge about neural networks, backpropagation algorithms, and applications. This article discusses the world of deep learning and is helpful for those trying to gain an initial level of knowledge about this subject.

Machine Learning Basics | SkillUp

The Machine Learning SkillUp course provided by Simplilearn includes an overview of supervised and unsupervised learning, plus algorithms and model evaluation. 

For individuals who have little or no clue of what Artificial Intelligence is, It provides the students with the necessary basic tools to enable them to grasp the core principles of AI.

Conclusion: Best AI Courses

All these courses are useful for novices who have a dream of AI or have a tiny experience and to those who want to bring their expertise to another level in this fast-changing field. 

It is wise to exploit these resources as a way of preparing for future careers in Artificial Intelligence, given that the resource will assist in averting obsolescence and help realize more real impacts of artificial intelligence in today’s world. 

Check out our excellent selection of programs and UX design certification, and sign up now!