The field of Artificial Intelligence (AI) has made remarkable and significant differences in various global industries as of today. With constant development every day, it aims to understand smart technology and contribute to the society.
Since AI encompasses a comprehensive academic paradigm and utilizes a multidisciplinary approach in learning, you may find it an interesting experience to learn all about smart machines. While the tip of the iceberg shows that AI exclusively studies intelligent tech, the disciplines umbrella also makes inquiries on intelligent entities in general, which includes us, humans.
If all these interest you, you will find taking online AI courses an enjoyable and fulfilling experience. In these online AI courses, youll learn all about algorithms, natural language processing, reinforcement learning, deep neural networks, image processing and recognition systems.
So if youre up for it, lets check out the top 10 Artificial Intelligence courses available this year that you must take on.
First things first. If you plan on following the typical chronology of topics and if you do not have much background on the basics of AI, then Foundations of AI will be a great place for you to start.
While this course is specifically concerned with the fundamental subject matters under AI, it still encompasses a wide range of interesting topics such as understanding AI basics, the various applications and examples of AI, and how AI can transform our lives.
You will also be learning all about Watson AI services (what they are and what they can be used for), along with understanding and using AI-powered chat bot technology.
Expect that you will be experiencing a bit of hands-on training through interactions with several AI functions in unique environments or media, as well as programming and deploying an AI-enabled chat bot programs on different sites.
The course is a 4-month Professional Certificate Program with an expected allocation of 4 to 6 hours per week. You can complete the program in your own pace and thus makes it an ideal program for working professionals who wants to pursue a side track in AI.
IBM also offers 3 other foundational or introductory AI courses that can be taken alongside with this course:
(1) AI for Everyone: Master the Basics;
(2) Introduction to Watson AI; and
(3) AI Chat bots without Programming.
Applied AI is another Professional Certificate Program from IBM. It focuses more on hands-on training and applications of AI complementary to learning basic AI concepts and theories by the book.
Some of the training youll go through include using Watson, Python, and OpenCV to build custom image classifiers. You will also learn:
This course is a Professional Certificate Program from IBM and can be completed in 8 months (depending on your own speed), with an expected allocation of 5 to 9 hours a week.
Columbia edX Artificial Intelligence 12-week course offers a more efficient, all-inclusive, comprehensive learning structure on the field. The program tackles on several important topics under AI such as:
Course schedule is instructor-led and classes are generally scheduled for 8 to 10 hours a week. And the best part is: the program is FREE! However, if you want to add a verified certificate at the end of the course, youll need to pay around 249 USD.
To give you a better idea on the topics to expect from the course, heres the programs tabulated syllabus:
Introduction to AI, history of AI, other course logistics
Intelligent agents, uninformed search
Heuristic search, algorithms
Adversarial search, games
Constraint Satisfaction Problems
Machine Learning: Basic concepts, linear models, perceptron, K nearest neighbors
Machine Learning: advanced models, neural networks, SVMs, decision trees and unsupervised learning
Markov decision processes and reinforcement learning
Logical Agent, propositional logic and first order logic
AI applications (Natural Language Processing)
AI applications (Vision or Robotics)
Review and Conclusion
(tabulated from https://www.edx.org/course/artificial-intelligence-ai)
The Bias and Discrimination in AI course by Universite de Montreal edX is a 4-week program that can be completed with 4-6 hour sessions a week.
The course highlights particularly rare (but interesting) topics under AI - gender, race, and socioeconomic-based bias, along with biased data-driven predictive models leading to decisions in different aspects of the field.
It also includes lessons on:
The programs syllabus consists of 4 main modules as tabulated below:
Module 1: The concepts of bias and fairness in AI
Different Types of Bias
Fairness criteria and metrics
Module 2: Fields where problems were diagnosed
Privacy, labour, and legal system
Public policy and health
Module 3: Institutional attempts to mitigate bias and discrimination in AI
Canadas Algorithmic Impact Assessment Framework
The Montreal Declaration for Responsible AI
Module 4: Technical attempts to mitigate bias and discrimination in AI
Fairness constraints in graph embeddings
Gender bias in text
(tabulated from https://www.edx.org/course/bias-and-discrimination-in-ai)
Universite de Montreal edX Deep Learning Essentials course is a self-paced 5-week program that can be completed with 4-6 hours a week. It primarily focuses on topics revolving around Deep Learning.
By the end of the program, you will have a better grasp and understanding of the basics, terminologies, and technical aspects on Deep Learning, identifying the types of neural networks to apply and solve different types of AI problems, and become more familiar with the topic through practical and hands-on sessions.
There are a total of 5 modules under the course with one taken every week.
Module 1: Machine Learning (ML) and Experimental Protocol
Introduction to ML
Module 2: Introduction to Deep Learning
Module 3: Introduction to Convolutional Neural Networks (CNN)
Introduction to CNN
Module 4: Introduction to Recurrent Neutral Networks
Sequence to Sequence Models
Concepts in Natural Language Processing
Module 5: Bias and Discrimination in ML
Difference of Fairness
Fairness in Pre-, In-, and Post-Processing
(tabulated from https://www.edx.org/course/deep-learning-essentials)
A Professional Certification Program for Deep Learning is also offered by IBM and it follows more or less the topics shown above.
This course is 7-week program from Harvard University edX and can be completed in a pace of 10-30 hours allocation per week. It mainly focuses on the initial steps professionals will take under the AI field to solve important real-world problems.
The course includes discussions on concepts of modern artificial intelligence and new technologies such as game-playing engines, handwriting recognition, and machine translation. It also offers hands-on projects and trainings in creating Python programs and other intelligent systems of their own. These trainings can help students gain more practical exposure beyond concepts and theories read in book.
Other specific topics under the program include: graph search algorithms, adversarial search, knowledge representation, logical inference, probability theory, Bayesian networks, Markov models, constraint satisfaction, machine learning, reinforcement learning, neural networks, and natural language processing.
This 12-week course from University of Pennsylvania edX is part of the Robotics MicroMasters program that teach and train students about the complex mobility challenges from deploying robotic structures in human environments.
You will be:
There are a total of 12 modules (including projects), with one discussed every week:
Module or Topic(s)
A Linear Time Invariant Mechanical System
A Nonlinear Time Invariant Mechanical System
Project #1: A Brachiating Robot
Qualitative Theory of Dynamical Systems
First Locomotion Model
A Vertical Hopping Controller
Project #2: From Bouncing Ball to Stable Hopper
The Spring Loaded Inverted Pendulum (SLIP)
Stepping Control of Fore-aft Speed
Project #3: Anchoring SLIP in Multi-Jointed Mechanisms
Project #4: A Running Controller for the Jerboa Robot
(tabulated from https://www.edx.org/course/robotics-locomotion-engineering)
Another program from PennX as part of the Robotics MicroMasters program, this course also focuses with robotic topics but emphasizes more on dynamics and control. Here, you will be learning how to design and engineer complex, dynamic robotic systems, mobile robots, drones (quadrotors), and how to design intelligent controls for these systems.
The course includes several topics under robotics such as robot dynamics, trajectory generation, motion planning, nonlinear control, developing real-time planning and controlling software modules.
It is a 12-week program with 12 modules (including a few projects) and can be completed with a schedule of 8 to 10 hours a week.
Module or Topic(s)
Introduction and Course Overview
Rigid Body Dynamics
Dynamics of Robot Arms
Project #1:Modeling of a Robot Arm
Introduction to Linear Control
State Space Modeling and Multivariable Systems
Project #2: Control and Trajectory Following for a Mobile Robot
Project #3: Planning and Control of a Quadrotor
(tabulated from https://www.edx.org/course/robotics-dynamics-and-control)
A part of the Algorithms and Data Structures MicroMasters program, this Dynamic Programming course is a 4-week self-paced program by University of San California, San Diego edX. It teaches the various applications of dynamic programming to AI algorithms, sequence alignments, and hidden Markov models.
The courses syllabus is as follows:
Week and Module
Week 1: Pairwise Sequence Alignment
A review of dynamic programming, and applying it to basic string comparison algorithms.
Week 2: Advanced Sequence Alignment
Learn how to generalize your dynamic programming algorithm to handle a number of different cases, including the alignment of multiple strings.
Week 3: Introduction to Hidden Markov Models
Learn what a Hidden Markov model is and how to find the most likely sequence of events given a collection of outcomes and limited information.
Week 4: Machine Learning in Sequence Alignment
Formulate sequence alignment using a Hidden Markov model, and then generalize this model in order to obtain even more accurate alignments.
(tabulated from https://www.edx.org/course/dynamic-programming-applications-in-machine-learning)
For a more comprehensive and all-inclusive course, this program made by Columbia University edX can be an umbrella course to take if you want to gain general and exhaustive knowledge and training on artificial intelligence.
The course offers solid understanding on the concepts, theories, and guiding principles of AI. It will train you in applying concepts of machine learning to grounded and hands-on experiences and attempts to bring about student proficiency beyond the rules of the book such as designing and harnessing the power of Neural Networks.
In a broader sense, the course aims to give you a better and stronger grasp on the extensive applications of AI in each unique field.