Top 10 Free Online Artificial Intelligence Courses for 2019 - LunaticAI

Top 10 Free Online Artificial Intelligence Courses for 2019

Hi Friends, As we all know nowadays Artificial Intelligence is one of the Trending topics all over the World. Also, the number of Students and other people are showing more interest in these Topics. So to explore this topic more, we have made a great collection of Free Artificial Intelligence Courses which we want to share with you.

These courses are from different websites including Udemy, Coursera, EDX and more. Don't worry these courses are free of cost. You need to invest only one thing that is time to start and complete this course. These Artificial Intelligence courses are for all that is for beginners, intermediate, and advanced level. These courses will help you to improve your skills a lot. So Just check out the below-given links.


List of Top 10 Free Artificial Intelligence Courses for Beginners, Intermediate and Advanced level are as follows

1. Learn with Google AI

Course by: Google


At Google AI, we’re conducting research that advances the state-of-the-art in the field, applying AI to products and to new domains, and developing tools to ensure that everyone can access AI.


Explore Course: AI by Google


2. Introduction to Artificial Intelligence


Course by: Udacity


From Which University: Stanford University

Syllabus of this course:

Part 1: Fundamentals of Artificial Intelligence


1. Overview of AI
2. Statistics, Uncertainty, and Bayes networks
3. Machine Learning
4. Logic and Planning
5. Markov Decision Processes and Reinforcement Learning
6. Hidden Markov Models and Filters
7. Adversarial and Advanced Planning


Part 2: Applications of AI


1. Image Processing and Computer Vision
2. Robotics and Robot Motion Planning
3. Natural language Processing and Information Retrieval


Subject Professor: Sebastian Thrun and Peter Norvig


Explore Course: AI by Stanford

3. Artificial Intelligence

Course By: Edx


From Which University: ColumbiaX


Learn the fundamentals of Artificial Intelligence (AI), and apply them. Design intelligent agents to solve real-world problems including, search, games, machine learning, logic, and constraint satisfaction problems


Basic Information About this Course:


Que: What do self-driving cars, face recognition, web search, industrial robots, missile guidance, and tumor detection have in common?


Ans: They are all complex real-world problems being solved with applications of intelligence (AI).


About this Course:

This course will provide a broad understanding of the basic techniques for building intelligent computer systems and an understanding of how AI is applied to problems.

You will learn about the history of AI, intelligent agents, state-space problem representations, uninformed and heuristic search, game playing, logical agents, and constraint satisfaction problems.


Hands-on experience will be gained by building a basic search agent. The adversarial search will be explored through the creation of a game and an introduction to machine learning includes work on linear regression.


What You Will Learn in this Course?


a. Introduction to Artificial Intelligence and intelligent agents, history of Artificial Intelligence


b. Building intelligent agents (search, games, logic, constraint satisfaction problems)


c. Machine Learning algorithms


d. Applications of AI (Natural Language Processing, Robotics/Vision)


e. Solving real AI problems through programming with Python


Course Syllabus:


Week 1: Introduction to AI, history of AI, course logistics
Week 2: Intelligent agents, uninformed search
Week 3: Heuristic search, A* algorithm
Week 4: Adversarial search, games
Week 5: Constraint Satisfaction Problems
Week 6: Machine Learning: Basic concepts, linear models, perceptron, K nearest neighbors
Week 7: Machine Learning: advanced models, neural networks, SVMs, decision trees, and unsupervised learning
Week 8: Markov decision processes and reinforcement learning
Week 9: Logical Agent, propositional logic and first-order logic
Week 10: AI applications (NLP)
Week 11: AI applications (Vision/Robotics)
Week 12: Review and Conclusion


Explore Course: AI by ColumbiaX

4. Artificial Intelligence for Beginners

Course By: Lynda (LinkedIn)


Basic Information About this Course:


This course will introduce you to some of the key concepts behind artificial intelligence, including the differences between "strong" and "weak" AI. You'll see how AI has created questions around what it means to be intelligent and how much trust we should put in machines. Instructor Doug Rose explains the different approaches to AI, including machine learning and deep learning, and the practical uses for new AI-enhanced technologies. Plus, learn how to integrate AI with other technology, such as big
data, and avoid some common pitfalls associated with programming AI.

What You Will Learn in this Course?


a. The history of AI
b. Machine Learning
c. Technical Approaches to AI
d. AI in Robots
e. Integrating AI with Big Data
f. Avoiding Pitfalls


Explore Course: AI by LinkedIn

5. The Beginners Guide to Artificial Intelligence in Unity


Course By: Udemy


Basic Information About this Course:


Do your non-player characters lack drive and ambition? Are they slow, stupid and constantly banging their heads against the wall? Then this course is for you. Join Penny as she explains, demonstrates and assists you to create your very own NPCs in Unity with C#. All you need is a sound knowledge of Unity, C# and the ability to add two numbers together.


In this course, Penny reveals the most popular AI techniques used for creating believable character behavior in games using her internationally acclaimed teaching style and knowledge from over 25 years working with games, graphics and having written two award-winning books on games AI. Through-out you will follow along with hands-on workshops designed to teach you about the fundamental AI techniques used in today's games. You'll join in as NPCs are programmed to chase, patrol, shoot, race, crowd and much more.


What You Will Learn in this Course?


a. Design and program NPCs with C# in Unity
b. Implement AI related Unity Asset plugins into existing projects
c. Explain How AI is applied in Computer Games
d. Work with a variety of AI techniques for developing navigation and decision making abilities in NPCs


Explore Course: AI by Udemy


6. Advanced AI Tutorial: Deep Reinforcement Learning in Python

Course By: Udemy

Basic Requirements for this Course:


1) Know reinforcement learning basics, MDPs, Dynamic Programming, Monte Carlo, TD Learning


2) Calculus and probability at the undergraduate level


3) Experience building machine learning models in Python and Numpy


4) Know how to build a feedforward, convolutional, and recurrent neural network using Theano and Tensorflow


What you will Learn in this Course?


a. Build various deep learning agents (including DQN and A3C)
b. Q-Learning with Deep Neural Networks
c. Reinforcement Learning with RBF Network
d. Apply a variety of advanced reinforcement Learning algorithms to any problems
e. Policy Gradient Methods with Neural Networks
f. Use Convolutional Neural Networks with Deep Q-Learning


Explore Course: AI by Udemy


7. Introduction to Artificial Intelligence

Course By: Edx


From Which Company: Microsoft


Subject Professor: Graeme Malcolm (Senior Developer at Microsoft)


Basic Information About this Course:


Artificial Intelligence will define the next generation of software solutions. This computer science course provides an overview of AI and explains how it can be used to build smart apps that help organizations be more efficient and enrich people’s lives. It uses a mix of engaging lectures and hands-on activities to help you take your first steps in the exciting field of AI.


Discover how machine learning can be used to build predictive models for AI. Learn how software can be used to process, analyze, and extract meaning from natural language; and to process images and video to understand the world the way we do.


Find out how to build intelligent bots that enable conversational communication between humans and AI systems.

What You Will Learn in this Course?


a. You will learn to Build simple machine learning models with Azure Machine Learning;


b. To Use Python and Microsoft cognitive services to work with text, speech, images, and video;


c. To Use the Microsoft Bot Framework to implement conversational bots.


Syllabus of this Course:


1. Introduction
2. Machine learning - The Foundation of AI
3. Text and Speech - Understanding Language
4. Computer Vision - Seeing the world through AI
5. Bots - Conversation as a platform
6. Next Steps

Explore Course: AI by Microsoft


8. Artificial Intelligence A-Z: Learn How to Build an AI

Course By: Udemy


Basic requirements of this Course:


1) High School Maths
2) Basic Python Knowledge

What you will learn in this Course?


a. You will understand the theory behind Artificial Intelligence
b. You will learn how to build AI
c. Make a virtual self-driving car
d. Solve Real-World Problems with AI
e. Q-Learning
f. Deep Convolutional Q-Learning
g. A3C
h. Deep Q-Learning
i. Master the State of Art AI Models
j. Make an AI beat games

Explore Course: AI by Udemy


9. Artificial Intelligence: Reinforcement learning in Python

Course By: Udemy


Basic Requirements for this Course:

1) Calculus
2) Probability
3) Object-Oriented Programming
4) Python coding
5) Lumpy Coding
6) Linear regression
7) Gradient Descent


What you will Learn in this course?

a. Apply gradient-based supervised machine learning methods to reinforcement learning

b. Understand the relationship between reinforcement learning and psychology


c. Understand reinforcement learning on a technical level Implement 17 different reinforcement learning algorithms


Explore Course: AI by Udemy

10. Introduction to Artificial Intelligence


Course By: NPTEL


From Which University: IIT Kharagpur


Syllabus of this Course:


The course will cover basic ideas and techniques underlying the design of intelligent computer systems.

Syllabus includes:

1. Introduction to AI and intelligent agents.

2. Problem Solving: Solving Problems by Searching, heuristic search techniques, constraint satisfaction problems, stochastic search methods.

3. Game Playing: minimax, alpha-beta pruning.

4. Knowledge and Reasoning: Building a Knowledge Base: Propositional logic, first-order logic, situation calculus. Theorem Proving in First-Order Logic.

5. Planning, partial-order planning.

6. Uncertain Knowledge and Reasoning, Probabilities, Bayesian Networks.

7. Learning: Overview of different forms of learning, Learning Decision Trees, Neural Networks.

8. Introduction to Natural Language Processing.

Explore Course: AI by IIT


11. Artificial Intelligence

Course By: NPTEL


From Which University: IIT Kharagpur


The course covers lessons in Introduction to Artificial Intelligence, Problem Solving by Search, Searching with Costs, Heuristic Search: A* and Beyond, Searching Game Trees, Knowledge-Based Systems: Logic and Deduction, First-Order Logic, inference in First-Order Logic, Logic Programming: Prolog, Prolog: Exercising Control, GraphPLAN, and SATPlan, Reasoning with Bayes Networks.

Syllabus of this Course:

Topic 1: Introduction to Artificial Intelligence
Topic 2: Problem Solving by Search
Topic 3: Searching with Costs
Topic 4: Informed State Space Search
Topic 5: Heuristic Search: A* and Beyond
Topic 6: Problem Reduction Search: AND/OR Graphs
Topic 7: Searching Game Trees
Topic 8: Knowledge-Based Systems: Logic and Deduction
Topic 9: First Order Logic
Topic 10: Inference in First-Order Logic
Topic 11: Resolution-Refutation Proofs
Topic 12: Logic Programming: Prolog
Topic 13: Prolog Programming
Topic 14: Prolog: Exercising Control
Topic 15: Additional Topics
Topic 16: Introduction to Planning
Topic 17: Partial Order Planning
Topic 18: GraphPLAN and SATPlan
Topic 19: SATPlan
Topic 20: Reasoning under uncertainty
Topic 21: Bayesian Networks
Topic 22: Reasoning with Bayes Networks
Topic 23: Reasoning under uncertainty - Issues
Topic 24: Learning: Decision Trees
Topic 25: Learning-Neural Networks
Topic 26: Back Propagation Learning


Explore Course: AI by IIT

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