Artificial intelligence is the world’s future. AI is now used in almost every app and website for the majority of its functionalities. They’re used for facial recognition locks, registering and verifying your security for transactions, and, more recently, putting your face on various characters in gaming and non-gaming applications. All of this is made feasible by artificial intelligence.

Below given are the best paid online courses for Artificial Intelligence in 2022.

1. Artificial Intelligence Certification Program by Stanford University:

This is the greatest artificial intelligence course, and it is perfect for computer programming and language programming students, as well as software engineers who will ultimately work with AI. Stanford University offers an AI certification programme taught by famous Professor Andrew Ng.

The course includes topics like:

  • Knowledge representation, machine learning
  • Models of logic and probability.
  • Natural language processing, robotics, and visual learning

After finishing the course, students will be able to apply for positions in AI programming, robotic engineering, constructing AI for practical applications, and its implementation in business modules.

If you want to acquire your degree in artificial intelligence from a respected college, this is a strong contender.

Prerequisites:

  • A Bachelor’s degree with a grade point average of 3.0 or above.
  • Advanced probability comprehension
  • Advanced linear algebra and statistics.
  • Programming experience in C/C++, Java, Python, or other equivalent languages.

2. Artificial Intelligence A-Z: (Coursera)

This course teaches students how to use Artificial Intelligence techniques such as Machine Learning, Data Science, and Deep Learning to construct AI designs for real-world applications.

The course includes topics like:

  • Artificial intelligence and its applications
  • Designs for Artificial Intelligence
  • Intuition Q-learning, Deep Q-learning, and Deep Convolutional Q-learning are three types of Q-learning.
  • Learning how to use A3C.
  • Advanced AI models can be controlled.
  • Construct virtual self-driving automobiles.
  • AI programming is used to test and defeat games.
  • Using diverse AI systems to actively solve real-world problems.

Candidates can use their broad understanding of AI to create and market real-world applications after completing the course. They can also apply for careers in advanced AI programming and contribute to the development of real-world AI technology.

If you’re new to AI, our artificial intelligence training course can help you get started right away.

Prerequisites: Basic Python understanding and high school math.

3. Artificial Intelligence 2018: Build the most powerful AI:

This course covers Augmented Random Search (ARS), which is utilized by global corporations to construct complex Artificial Intelligence models.

The course includes topics like:

  • Discover how to create Artificial Intelligence Programming.
  • Create sophisticated artificial intelligence algorithms.
  • Theory and implementation of ARS, as well as how to utilize the algorithm in practice.
  • Preparing the AI model to tackle issues in the same way as Google Deep Mind does.

Candidates who complete the courses can apply for careers in AI programming or use their skills to create AI algorithms that compete with Google Deep Mind to tackle challenging challenges.

Prerequisites: It include familiarity with Python coding and scripting, basic mathematics, and a PC capable of running Anaconda.

4. The Beginner’s Guide to Artificial Intelligence in Unity:

This course teaches you how to use C# to construct and navigate non-player characters in Google Play and App Store games. This course teaches students how to build NPCs and integrate them into current software, as well as how to navigate NPCs and programme decision-making abilities.

The course includes topics like:

  • Mathematical vectors
  • Using vectors to move characters in different directions and go to destination areas.
  • The Unity Vehicle and Waypoint systems are used to navigate automobiles and construct racing programs.
  • In-depth understanding of waypoints via graph and pathfinding, as well as the creation of waypoints in 2D.
  • Moving from Waypoint to NavMesh and learning to animate and sync agent speed in different sizes.
  • Wandering, escaping, hiding, pursues, and other complex behavioral patterns
  • Crowd simulation to create city crowds and guide them through various difficulties.
  • Convert Finite State Machines to work with NavMesh.
  • Introduction to behavior trees by carefully building nodes that impact behavioral disorders.
  • Action with a Purpose Playing with global states and various hosts, and adding actions to do.

After finishing the course, you will be able to use these strategies in creating games or modifying NPC behavior in pre-existing games. You can then apply for positions in game design, game testing, and other related fields.

Prerequisites: Experience with C# and knowledge with the Unity Game Development Engine are required.

5. Master Class in AI by Udemy:

This course is the ideal bundle for learning how to create strong AI and hybrid AI models.

The course includes topics like:

  • Fully linked neural networks: understanding and implementation
  • Using Genetic Algorithms, Evolutionary Strategies, and Policy Gradients.
  • NeuroEvolution and deep learning of recurrent neural networks
  • To become an effective AI programmer, practice mixing density networking and more sophisticated formulae.
  • Constructing Hybrid Intelligence Systems

Later, candidates will be prepared to execute inventive and progressive programming to meet the ever-changing demands of technology. They can obtain the most effective tools for developing advanced AI models and applying them to increasingly crucial data science and artificial intelligence employment responsibilities.

Prerequisites: High school math knowledge and coding experience.

6. Intro to AI for managers by Udemy:

This course provides a thorough understanding of the technical components of AI via in-depth machine learning and deep learning techniques.

The course includes topics like:

  • Techniques for identifying possibilities and utilizing AI to advance your business initiative.
  • Teaches how to handle AI projects more effectively in order to get remarkable results.
  • Preventing numerous underfit and overfit candidacy difficulties, as well as regularizing the business module
  • Python programming and the Scikit library for more efficient programming.
  • Convolutional neural networks, multi-layer neural networks, recurrent neural networks, and deep learning are all examples of neural networks.

Students will learn how to optimize their company environment for optimum utility and production after finishing the course. They will also be skilled in project management for AI.

Prerequisites: A basic understanding of mathematics and algorithms, as well as their technical definitions.