TOP 15 Udemy Artificial Intelligence Courses

According to Gartner,there is huge enterprise-level interest in artificial intelligence projects and their potential to fundamentally change the dynamics of business value. However,biggest pain point that emerged from Gartner’s 2018 CIO survey was the lack of specialized skills in AI, with 47% of CIOs reporting that they needed new skills for AI projects.With Gartner predicting AI as #2 in Top 10 Strategic Technology Trends for 2019.There is need for AI engineers to build, implement, and maintain AI projects.Here’s best compilation of 15 Udemy Artificial Intelligence Courses.

TAKE ACTION AND START ENROLLING TODAY! All of the below listed courses are running at discount of about 90%. And for any reason you are unhappy with the course, Udemy has a 30 day Money Back Refund Policy, So no questions asked and no Risk to you. You got nothing to lose.

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#1.Artificial Intelligence A-Z™: Learn How To Build An AI

Combine the power of Data Science, Machine Learning and Deep Learning to create powerful AI for Real-World applications!

Here is what you will get with this course:

1. Complete beginner to expert AI skills – Learn to code self-improving AI for a range of purposes. In fact, we code together with you. Every tutorial starts with a blank page and we write up the code from scratch. This way you can follow along and understand exactly how the code comes together and what each line means.

2. Code templates – Plus, you’ll get downloadable Python code templates for every AI you build in the course. This makes building truly unique AI as simple as changing a few lines of code. If you unleash your imagination, the potential is unlimited.

3. Intuition Tutorials – Where most courses simply bombard you with dense theory and set you on your way, we believe in developing a deep understanding for not only what you’re doing, but why you’re doing it. That’s why we don’t throw complex mathematics at you, but focus on building up your intuition in coding AI making for infinitely better results down the line.

4. Real-world solutions – You’ll achieve your goal in not only 1 game but in 3. Each module is comprised of varying structures and difficulties, meaning you’ll be skilled enough to build AI adaptable to any environment in real life, rather than just passing a glorified memory “test and forget” like most other courses. Practice truly does make perfect.

5. In-course support – We’re fully committed to making this the most accessible and results-driven AI course on the planet. This requires us to be there when you need our help. That’s why we’ve put together a team of professional Data Scientists to support you in your journey, meaning you’ll get a response from us within 48 hours maximum.

Requirements

• High School Maths
• Basic Python knowledge

Created by: Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team, SuperDataScience Support

Ratings : 4.3 (7,778 ratings)

#2.Deep Learning and Computer Vision A-Z™: OpenCV, SSD & GANs

Become a Wizard of all the latest Computer Vision tools that exist out there. Detect anything and create powerful apps.

With this brand new course you will not only learn how the most popular computer vision methods work, but you will also learn to apply them in practice!

Requirements

• Only High School Maths
• Basic Python programming knowledge

Created by: Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team

Ratings :4.4 (2,272 ratings)

#3.Artificial Intelligence 2018: Build the Most Powerful AI

Learn, build and implement the most powerful AI model at home. Compete with multi-billion dollars companies using ARS.

This game-changing AI called Augmented Random Search, ARS for short.And in a very simple implementation, it is able to do an exact same thing that Google Deep Mind did in their accomplishment last year  which is to train an AI to walk and run across a field.

Requirements

• Python prior coding or scripting experience is required.
• High school level math skills will be required.
• PC (Windows, Mac or Linux), where Anaconda could be installed and run

Created by: Hadelin de Ponteves, Kirill Eremenko, SuperDataScience Team

Ratings :4.5 (384 ratings)

#4.Artificial Intelligence I: Basics and Games in Java

A guide how to create smart applications, AI, genetic algorithms, pruning, heuristics and metaheuristics

This course is about the fundamental concepts of artificial intelligence. This topic is getting very hot nowadays because these learning algorithms can be used in several fields from software engineering to investment banking. Learning algorithms can recognize patterns which can help detecting cancer for example. We may construct algorithms that can have a very  good guess about stock price movement in the market.

In the first chapter we are going to talk about the basic graph algorithms. Several advanced algorithms can be solved with the help of graphs, so as far as I am concerned these algorithms are the first steps.

Second chapter is about local search: finding minimum and maximum or global optimum in the main. These searches are used frequently when we use regression for example and want to find the parameters for the fit. We will consider basic concepts as well as the more advanced algorithms: heuristics and meta-heuristics.

The last topic will be about minimax algorithm and how to use this technique in games such as chess or tic-tac-toe, how to build and construct a game tree, how to analyze these kinds of tree like structures and so on. We will implement the tic-tac-toe game together in the end.

Requirements

• Basic Java (SE)
• Some basic algorithms ( maximum/minimum finding )
• Basic math ( functions )

Created by: Holczer Balazs

Ratings : 4.3 (362 ratings)

#5.Artificial Intelligence II – Neural Networks in Java

Hopfield networks, neural networks, backpropagation, optical character recognition, feedforward networks

This course is about artificial neural networks. Artificial intelligence and machine learning are getting more and more popular nowadays. In the beginning, other techniques such as Support Vector Machines outperformed neural networks, but in the 21th century neural networks again gain popularity. In spite of the slow training procedure, neural networks can be very powerful. Applications ranges from regression problems to optical character recognition and face detection.

In the first part of the course you will learn about the theoretical background of neural networks, later you will learn how to implement them.

Requirements

• Basic Java

Created by: Holczer Balazs

Ratings : 4.0 (244 ratings)

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#6.Technology Trends

This course is an exploration of the technology and philosophy that will shape the next 20 to 30 years. We’ll develop our big picture understanding of where the world is going and when. The course will also challenge us to ask some of the deepest questions that we’ll be faced with in the near future; who are we? what do we want? and how can we create what we want?

Here are some of the topics included:

Nanotechnology – How will the shrinking of our technology change our tools and our world?

Artificial Intelligence – A.I. will completely reshape our relationship with computers, our cities, and our daily lives. What will this look like and when?

Immortality & Aging – For the first time in history, we have the chance to reprogram our biology away from aging and disease. What questions will this pose for us? What are the steps to defeating death?

Internet of Things – What happens when the physical world comes online and becomes intelligent?

Augmented & Virtual Realities – Our technology isn’t something that only exists in the physical reality we’re used to. With virtual and augmented reality, we’re enhancing the real world and creating entirely new worlds.

Requirements

• Curiosity for the future of humans and technology
• Open mind to asking the deepest questions

Created by: Thomas O’Brien

Ratings : 3.7 (73 ratings)

#7.Application Development with IBM WATSON

Chatbot, Visual Analyser, Tone Analyser, Face Detection, Voice Detection and many more..

This course is focused learning and exploring IBM Watson services with practical approach and demonstration of each services available on cloud. You could integrate these services in your Web, Android, IoT, Desktop Applications like Face Detection, ChatBot, Voice Detection, Text to custom Speech (with pitch, emotions, etc), Speech to text, Sentimental Analysis on Social media or any textual data.

Watson services include:

1. Conversation

2. Discovery

3. Personality Insight

4. Text-to-Speech

5. Speech-to-Text

6. Tone Analyser

7. Visual Analyser

8. Natural Language Understanding

9. Language Translator

10. Knowledge Studio

11. Natural Language Classifier 

Requirements

• Nothing required at all! but if you have a background in computer science or development, it would be beneficial, but not required at all.

Created by: Harshit Srivastava

Ratings : 3.8 (66 ratings)

#8.ZERO to HERO Python 3 FULL STACK MASTERCLASS 45 AI projects

HTML To Artificial Intelligence Deep Learning bootcamp Cornell University course w/Machine Learning! New for 2018!

This course will be continually updated and we answer all questions.  We will continue updating content based on both user demand and changes in machine learning and AI.  If you have taken a previous bootcamp but still are struggling, this course will fill in the holes and have you applying Python on lots of different projects.  You will learn faster by 

This is the only fullstack course that teaches you everything from basic frontend HTML to Python 3, Machine learning, Tensor Flow, and Artificial Intelligence / Recurrent Neural Networks!  

Requirements

• Have a PC or mac. Must have desire to learn programming. HD monitor is preferred.

Created by: Gopal Shangari

Ratings : 4.0 (66 ratings)

#9.Artificial Intelligence:Deep Learning in Real World Business

Learn how to deploy deep learning business applications for real world purposes.

In this course, you will learn:

• What is deep learning and how to implement it
• The core concepts of deep learning
• Basic of Deep Learning and modern best practices with a digit classification problem of MNIST
• The types of problems deep learning/AI solves
• Learn about Data Science, its challenges and how to tackle them
• Apply deep learning to other domains like Language Modeling, ChatBots and Machine Translation using the one of the powerful architectures of DL, RNN

At the end of this course, you will learn all the essentials needed to explore and understand what is deep learning and will perform deep learning tasks first hand.

Requirements

• Nothing. No prior knowledge about deep learning required.

Created by: Eduero Academy, Inc.

Ratings : 4.1 (56 ratings)

#10.Artificial Intelligence (AI) in Software Testing

The Future of Automated Testing with Machine Learning – Implementing Artificial Intelligence (AI) in Test Automation

This course is designed for both testers and developers. Tester who want to develop their testing skills in the test automation with Artificial Intelligence (AI) and Developer who want to execute their unit test in automated way using Artificial Intelligence (AI).

This course will teach you how AI-assisted test automation can transform the UI. This course will also teach you Artificial Intelligence (AI) and it’s relationship with Machine Learning, Deep Learning and Data Science. After you have completed this course you should be able to build test automation projects for your company’s applications using Artificial Intelligence (AI). This course should also help you for your AI test automation job interview.

Requirements

• All should need to know is What is importance of Software Testing and What is the benefits of implementing Test Automation over manual testing.

Created by: Sujal Patel

Ratings : 4.0 (36 ratings)

#11.Artificial Intelligence III – Deep Learning in Java

Deep learning fundamentals, focusing on convolutional neural networks and recurrent neural networks, LTSM, GRUs

This course is about deep learning fundamentals and convolutional neural networks. Convolutional neural networks are one of the most successful deep learning approaches: self-driving cars rely heavily on this algorithm. First you will learn about densly connected neural networks and its problems. The next chapter are about convolutional neural networks: theory as well as implementation in Java with the deeplearning4j library. The last chapters are about recurrent neural networks and the applications!

Requirements

• Some math (derivatives and matrix operations)
• Java basics (classes, objects etc.)

Created by: Holczer Balazs

Ratings : 4.2 (34 ratings)

#12.Artificial Intelligence Bootcamp 44 projects Ivy League pro

Be a Machine Learning, Matplotlib, NumPy, and TensorFlow pro. Use AI for programming, business or science!

This video course is built for those with a NO understanding of artificial intelligence or Calculus and linear Algebra.  We will introduce you to advanced artificial intelligence projects and techniques that are valuable for engineering, biological research, chemical research, financial, business, social, analytic, marketing (KPI), and so many more industries.  Knowing how to analyze data will optimize your time and your money.  There is no field where having an understanding of AI will be a disadvantage. 

Requirements

• Some experience with Python is needed. Statistics would be helpful but not required.

Created by: Gopal Shangari

Ratings : 3.7 (24 ratings)

#13.Artificial intelligence in Game development- Tic Tac Toe AI

Artificial intelligence & Javascript 2D Game Development – MinMax algorithm – “Computer vs You” Tic Tac Toe AI game

This course combines Artificial intelligence and Javascript and takes you into the world of 2D game development and creating 2D AI games. 

You’ll be able to:

1. Learn the basics of artificial intelligence, its terminologies, the various terms used in the field etc. 

2. Learn what the MiniMax algorithm is and how it’s used in developing Zero sum artificial based games in the real world.

3. Learn how to apply the MiniMax algorithm in a 2D web game like Tic Tac Toe 

4. Learn how to create an unbeatable AI opponent in your games 

5. Learn the basics of Javascript and HTML5 canvas and how to apply it in your Tic Tac Toe game project

6. Improve your logical problem solving skills

7. Create a complete dynamic Tic Tac Toe game app with an unbeatable AI with Javascript, HTML5 canvas and css

8. Improve your web app development, web game development & javascript skills

9. Improve your front end design and development skills

10. How to design the game logic for the game and implement it as code

11. Learn HTML5, CSS3 and much more while developing your game

12. Add artificial intelligence to your resume with this project as proof of your knowledge 

Requirements

• A computer and an internet connection to watch this course
• Ability to use computers and download the free software mentioned in the course
• A text editor like Notepad or notepad++ or Brackets to write the programs on

Created by: Aarthi Elumalai

Ratings : 4.1 (23 ratings)

#14.Artificial Intelligence #1: Linear & MultiLinear Regression

Regression techniques for students and professionals. Learn Linear & Multilinear Regression and code them in python

In this Course you learn Linear Regression & Multilinear Regression
You learn how to estimate and predict simple and single variable regression to find the possible future output Next you go further  
You will learn how to estimate output of Multivariable model by using Multilinear Regression

In the first section you learn how to use python to estimate output of your system. In this section you can estimate output of:

• Random Number
• Diabetes
• Boston House Price
• Built in Dataset

In the Second section you learn how to use python to estimate output of your system with multivariable inputs.In this section you can estimate output of:

• Global Temprature
• Total Sales of Advertising Campaign
• Built in Dataset

Requirements

• You should know about basic statistics
• You must know basic python programming
• Install Sublime and required library for python
• You should have a great desire to learn programming and do it in a hands-on fashion, without having to watch countless lectures filled with slides and theory.
• All you need is a decent PC/Laptop (2GHz CPU, 4GB RAM). You will get the rest from me.

Created by: Sobhan N

Ratings : 3.9 (23 ratings)

#15.Artificial Intelligence IV – Reinforcement Learning in Java

All you need to know about Markov Decision processes, value- and policy-iteation as well as about Q learning approach

This course is about Reinforcement Learning. The first step is to talk about the mathematical background: we can use a Markov Decision Process as a model for reinforcement learning. We can solve the problem 3 ways: value-iteration, policy-iteration and Q-learning. Q-learning is a model free approach so it is state-of-the-art approach. It learns the optimal policy by interacting with the environment. So these are the topics:

• Markov Decision Processes
• value-iteration and policy-iteration
• Q-learning fundamentals
• pathfinding algorithms with Q-learning
• Q-learning with neural networks

Requirements

• Basics AI knowledge: neural networks in the main

Created by: Holczer Balazs

Ratings : 4.2 (22 ratings)

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