7 Best AI Engineering Courses [2021 JULY] [UPDATED]

Best AI Engineering course tutorial class certification training online

Artificial Intelligence works as an added advantage for engineers, as it delivers additional capabilities and skills. That’s why most institutions and organizations are offering AI Engineering programs for individuals to gain advanced skills. If you are interested in learning AI Engineering skills, we can help you. After thorough research of multiple online platforms, we have created a list of some of the Best AI Engineering Courses, Classes, Programs, Tutorials, Training, and Specialization programs available online. The classes are prepared with high-quality video lectures and continuous assistance from the instructors. Also, the list includes both paid and free courses to help you choose a course effortlessly. Don’t forget to take a look at our compilation of Data Science Courses.


7 Best AI Engineering Courses [2021 JULY] [UPDATED]

1. IBM AI Engineering Professional Certificate by IBM (Coursera)

Created by industry professionals working with IBM, this comprehensive program will equip you with all the tools and skills required to succeed in your career as an AI or ML engineer. This program consists of six different courses that will help you master the essential concepts of machine learning and deep learning, such as supervised and unsupervised learning with programming languages like Python. You’ll also get a chance to work with hands-on projects that will help you gain essential data science skills by scaling machine learning algorithms on Big Data with Apache Spark. After completing the specialization, you’ll receive a digital certificate to share with employers and your LinkedIn profile.


Key USPs –

– A well-structured program that will describe machine learning, deep learning, neural networks, and ML algorithms like regression, classification, clustering, and dimensional reduction.

– Learn how to implement supervised and unsupervised machine learning models with SciPy and ScikitLearn.

– Learn how to apply popular machine learning and deep learning libraries, such as SciPy, ScikitLearn, Keras, PyTorch, and TensorFlow to industry problems.

– Be able to develop, train, and deploy different types of deep architectures, such as convolutional neural networks, recurrent networks, and autoencoders.


Duration: 8 months

Rating: 4.4 out of 5

You can Sign up Here


2. Start Building your AI Strategy (Kellogg School of Management)

If you want to gain a better perspective of AI technology to grow your career, this program from Kellogg School of Management is an excellent option. Joining this learning path will give you exposure to various AI and ML algorithms used to solve complex business problems. It is ideally designed for experienced executives, managers, and consultants who are involved in implementing AI across enterprise functions. It consists of 8 learning modules, during which you’ll get the opportunity to build a robust playbook to frame AI initiatives, identify the most impactful business problems, map your AI journey, and much more.


Key USPs –

– A step-by-step program that will lead you to breakthrough thinking about AI capabilities to help you thrive your organization in the era of AI.

– Learn about various frameworks to build an effective AI implementation plan while understanding the business applications and consequences that can be achieved with AI.

– Learn how to craft your AI journey, from strategy and capabilities to execution and organization.

– Be able to apply the AI capability Maturity Model to develop enterprise AI capabilities in a phased and systematic manner.

– Access live faculty teaching sessions, real-world applications, use cases, and practical frameworks to drive AI strategy.


Duration: 2 months, 4-6 hours/week

Rating: 4.6 out of 5

You can Sign up Here


Review: Easy to understand content and methodology, reinforced by real-world use cases. – Glenn J. Hoormann.


3. Post Graduate Program in AI and ML (Purdue University)

Prepared in collaboration with the IBM organization, this comprehensive program is designed for individuals looking for a PG Diploma in AI and ML. Taking this curriculum will help you unlock your potential as an AI and ML professional by teaching you various AI-based technologies, such as machine learning, deep learning, computer vision, natural language processing, and reinforcement learning. It is included with multiple modules and elective modules designed with a step-by-step approach to give you a better learning experience. During the classes, you will receive real-world quizzes, graded assignments, exercises, and hands-on projects to improve your knowledge.


Key USPs –

– A perfect blend of theory, practicals, and real-world applications to help you understand the core concepts of AI and ML.

– Get a better understanding of the Python programming language and its libraries, writing scripts with Jupyter-based lab environment.

– Cover essential aspects of deep learning to build mock neural networks and cross layers of data abstraction with a solid understanding of deep learning with TensorFlow.

– Attend the online interactive industry master class to gain insights into advancements in Data Science, AI, ad Machine Learning techniques.


Duration: 12 months, 5-10 hours/week

Rating: 4.4 out of 5

You can Sign up Here


4. Machine Learning: Fundamentals and Algorithms (Carnegie Mellon University)

Individuals who want to improve their skills in machine learning algorithms can take help from this program. Created by experienced professionals of Carnegie Mellon University, this online program will provide you with the technical acquaintance and analytical skills that will prepare you for the next generation of innovation. Though it requires functional knowledge of high-school-level linear algebra, calculus, probability, and statistics, you’ll equip advanced machine learning skills. During this 10-week online program, you will gain a skillset focused on fundamental machine learning methods. At the end of the curriculum, you’ll be able to implement the k-means algorithm and explain challenges in selecting the number of clusters.


Key USPs –

– Deepen your understanding of machine learning fundamentals and algorithms, Python programming skills, and more.

– Learn how to create and use a decision tree to make predictions with given labeled training examples.

– Get introduced to the K-NN algorithm and how to use it to classify points with a simple dataset while implementing a complete decision tree.

– Be able to determine how convexity affects optimization and implement linear regression with optimization by stochastic gradient descent.

– Earn a reward for completing each module in the program that will encourage you to move further.


Duration: 10 weeks, 5-10 hours/week

Rating: 4.5 out of 5

You can Sign up Here


5. Become a Machine Learning Engineer (Udacity)

Designed in collaboration with Kaggle and AWS, this nano degree program is all you need to become a professional machine learning engineer. Ideally prepared for managers, team leaders, and software engineers, this program will teach you advanced machine learning techniques and algorithms, such as how to package and deploy your models to a production environment. It is equipped with machine learning case studies that will enable you to apply machine learning methods to solve real-world tasks, discover data and organize both built-in and custom-made Amazon SageMaker models. Once you complete the program, you’ll have all the essential skills required to become a professional machine learning engineer.


Key USPs –

– A valuable program that focuses on teaching you the fundamental concepts of machine learning and its various algorithms.

– Learn how to write production-level code and practice object-oriented programming that can be integrated into machine learning projects.

– Learn to deploy machine learning models to a production environment with both built-in and custom-made Amazon SageMaker.

– Get one-on-one mentor support to guide you throughout the learning journey and answer your questions, motivate you, and keep you on track.


Duration: 3 months, 10 hours/week

Rating: 4.6 out of 5

You can Sign up Here


Review: I really enjoyed this program! Since I didn’t have any background related to data, I first took Udacity’s free courses such as Python, Statistics, SQL, Linear Algebra etc. – Chieko N.


6. Artificial Intelligence Nanodegree (Udacity)

Individuals interested in learning essential AI concepts from industry experts like Peter Norvig and Sebastian Thrun can benefit from this nano degree program. This program is intended to help you learn how to write useful AI programs with the algorithms powering everything from NASA’s Mars Rover to DeepMind’s AlphaGo Zero. In this program, the instructors will provide you with real-world projects to help you understand how to work with AI principles in real life. Also, it is included with a lot of quizzes, high-quality video lectures, quality assignments, and other rich learning content to improve your understanding of AI concepts.


Key USPs –

– A custom learning plan tailored to teach you all about artificial intelligence to help you grow your career.

– Learn how to use constraint propagation and search to build an agent that reasons like a human would do to solve any puzzle efficiently.

– Learn to extend your classical search to adversarial domains to build agents that can make business decisions without any human intervention, including DeepMind and AlphaGo agent.

– Get access to resume support, GitHub portfolio review, and LinkedIn profile optimization to help you advance your career and land a good job.


Duration: 3 months, 12-15 hours/week

Rating: 4.5 out of 5

You can Sign up Here


Review: It’s a very nice explanation, however the code provided needed more explanation. It is not easy to follow written code without documentation, but the boxes\units. Etc. structures proved to be very helpful. If I understood them better through explanation from the instructor in a video, the experience would have been perfect 🙂 – Emad T.



7. Artificial Intelligence Engineer (IBM)

Created in collaboration with IBM, this pragmatic course will help you master Data Science concepts with Python, Machine Learning, Deep Learning, and NLP with live sessions, practical labs, and projects. In this curriculum, you’ll gain in-depth knowledge of AI concepts, including the essentials of statistics required for data science and Python programming. During the video lessons, you’ll also learn how to use Python libraries like NumPy, SciPy, Scikit, and other machine learning techniques. The program is covered with real-world case studies to give you better exposure to the business problems that can be solved with AI principles.


Key USPs –

– A practical program prepared to help you learn and understand the core principles of artificial intelligence to help you become a professional AI Engineer.

– Learn about various machine learning techniques, such as supervised and unsupervised learning, advanced concepts that cover AI neural networks, TensorFlow, etc.

– Work with a wide range of industries applications, such as healthcare, transportation, insurance, logistics, and customer service.

– Be able to design and build intelligent AI agents, apply them to create practical AI projects and knowledge-based systems.


Duration: Self-paced

Rating: 4.6 out of 5

You can Sign up Here


Review: I joined Simplilearn with great expectations, as it was recommended to me by a collogue. However, after putting in many hours in the instructor-led training, projects, quizzes and reading materials, now I am feeling much more confident in my work environment. I am very pleased with the courses and hope it will help me in my future career growth. – Bibhu Dash.



The above courses and programs are obtained from the best e-learning resources to provide you the best learning experience. You can take up any learning path that best fits your requirements, and you won’t be disappointed.