82% Off Artificial Intelligence A-Z™ 2023: Build an AI with ChatGPT4 | Udemy Review & Coupon

The combination of Data Science, Machine Learning, and Deep Learning can be utilized to develop effective AI for practical applications.

This course covers:

This course is an excellent resource for those who want to gain comprehensive and specialized knowledge on a given topic. It offers 17 hours of on-demand videos, 20 articles, and 3 downloadable resources that will provide users with the necessary skills to grow their understanding of the subject. The course can be accessed both on mobile and TV devices, and includes closed captions for those who are hard of hearing, as well as a certificate of completion at the end. The combination of both audio and visual aid make it much easier for users to follow along, while the support from the different written resources helps solidify their understanding. This is an ideal option for those looking to develop or strengthen their expertise in the area they’re studying.

What you'll learn

With Artificial Intelligence (AI) taking over more of our everyday tasks, it’s becoming increasingly important to understand how AI works. With a bit of study and practice, this topic can be quite accessible even for novice coders and engineers. With the right guide, one can learn to develop an AI program and create all sorts of virtual creations. For example, you can use Neural Networks to make a virtual self driving car that learns from its environment or experiential learning algorithms to create AI that can beat complex video games. You could also use supervised and unsupervised machine learning techniques to solve real world problems. Additionally, after mastering the fundamentals of AI you’ll be able to explore the newest tools and techniques in the field such as generative adversarial networks, reinforcement learning, deep learning models such as convolutional neural networks (CNN) and recurrent neural networks (RNN), natural language processing (NLP), clustering algorithms such as K-Means clustering, Bayesian modelling techniques like Markov Chains/Models etc.

By studying Artificial Intelligence, one can become proficient in building advanced autonomous machines that are designed for intelligent behaviour without requiring human intervention or commands. More importantly though is that with an in -depth understanding of AI, you can develop effective algorithms and programs that can solve complex tasks such as natural language processing, image recognition, robotics, pattern recognition, game theory and much more.

About the author

Kirill Eremenko

He has a professional background in Data Science consulting, with expertise in industries such as finance, retail, and transportation. After receiving training from top analytics mentors at Deloitte Australia, the individual has shared their knowledge with thousands of aspiring data scientists on Udemy.

Through the combination of his academic background in Physics and Mathematics, along with his real-life experience, he delivers professional coaching in Data Science with a step-by-step approach. The teacher's focus on intuitive explanations is a strong aspect of his teaching style, ensuring a thorough understanding of complex topics.

In conclusion, he has a strong passion for Data Science and is eager to share his knowledge and enthusiasm with others.

Hadelin de Ponteves

Hadelin is an online entrepreneur who has developed over 30 highly rated educational e-courses on various modern technology subjects, including Artificial Intelligence, Machine Learning, Deep Learning, Blockchain, and Cryptocurrencies. He is dedicated to sharing this knowledge with the world and assisting as many individuals as he can. The courses have garnered subscriptions from over 1.7 million students.

Requirements

As a basic requirement for many coding-related courses and activities, having a strong background in mathematics is important. High school maths can provide the necessary foundation for understanding more complex concepts such as data structures, algorithms, or numerical analysis. With math, students learn important principles such as fundamental operations, linear equations, graphing techniques, calculus, probability and statistics. Math skills are particularly useful when it comes to software engineering as programming involves tasks such as looping commands and using conditional loops to find solutions to challenging problems.

Another important prerequisite for coding classes is basic knowledge of Python or any other programming language. Python is an incredibly versatile language that’s used for web development, artificial intelligence (AI), data science, game development and more. Learning Python helps individuals understand how various components of coding work together so that they can build efficient programs that meet their needs. For some activities like game development or AI research , even intermediate or advanced knowledge of the scripting language may be required. Understanding variables, lists, functions and objects are just some of the core aspects of learning Python programming which anyone wishing to take coding classes should master beforehand.

Description

This course provides an introduction to Artificial Intelligence (AI) concepts and intuition training. A wide range of topics are covered, from starting building AI with no coding experience using Python, to merging AI with OpenAI Gym for effective learning, and how to optimize your AI for its use in the real world. The course is designed to help individuals who are interested in diving headfirst into the increasingly popular field of AI without any previous expertise or knowledge about the technology.

This comprehensive tutorial-style course is suitable for both novice and advanced AI practitioners alike - it is a great way to get a thorough understanding of all the fundamentals that encompass the technology. The video lectures combined with hands-on guides focus on key insights and practical perspectives, which should enable users to quickly gain confidence when working with latest machine learning tools and frameworks such as TensorFlow or scikit-learn. All the essential skills needed to build efficient data science projects are discussed in-depth here, making this Kickstarter-approved resource perfect for anyone looking pinpoint their grasp on Artificial Intelligence.

This course includes the following materials:

Complete beginner to expert AI skills – Acquire the skill to program AI that can improve itself for various applications. We collaborate on coding with you. The process of starting a tutorial involves beginning with a blank page and writing the code from scratch. By following along, you can gain a clear understanding of how the code is assembled and the purpose of each line.

Code templates – In addition, downloadable Python code templates will be provided for every AI constructed during the course. Building unique AI is made easy by making a few alterations to the code. By letting your imagination run wild, the possibilities are endless.

Intuition Tutorials – Our approach to courses involves fostering a comprehensive comprehension of not just the how, but also the why behind the material, rather than inundating you with dense theory and sending you on your way. We prioritize developing your intuition in coding AI rather than presenting you with complex mathematics, resulting in improved outcomes in the future.

Real-world solutions – Your goal can be accomplished in three games, not just one. The modules contain diverse structures and levels of difficulty that enable the development of adaptable AI for real-life scenarios, as opposed to a simple memorization exercise commonly found in other courses. Repetition and effort can lead to improvement.

In-course support – Our goal is to create an AI course that is highly accessible and focused on achieving measurable results. It is necessary for us to be present and assist you as needed. We have assembled a team of skilled Data Scientists to assist you throughout your journey, ensuring that you receive a response from us within a maximum of 48 hours.

This course is intended for:

This course is designed for individuals who are interested in Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning. It provides essential knowledge and hands-on practice in each of these disciplines. After completing this course, participants should be able to build AI models that can support decision making in complex environments.