how to become a machine learning engineer

best machine learning engineer course class certification training online

Machine Learning Engineering is a career game-changer for highly ambitious Technology Professionals leading to better opportunities, more credibility, and significantly higher pay. To help you learn Machine Learning, we have done extensive research and brought to you the tried and tested Best Six Machine Learning Engineering Courses, Certifications, Classes, Tutorials, and Training programs available online for 2021.

10 Best Machine Learning Engineering Courses [2021 NOVEMBER][UPDATED]

1. Become a Machine Learning Engineer by Kaggle – AWS (Udacity)

This Nanodegree Program by Udacity teaches you the advanced algorithms of Machine Learning that help you become a proficient Machine Learning engineer. With this course, you will get to know the best techniques like packaging and deploying your inventions to a production environment. The instructors of this course are highly competent Machine Learning experts. Intermediate knowledge of Machine Learning Algorithms like Deep Learning, Supervised, and Unsupervised models, Python programming knowledge, and a minimum of 40-hour programming experience are the prerequisites to enroll in this course.

Key USPs –

– You will get to work on hands-on projects from the leading industry experts to enhance your tech skills.

– A technical mentor will provide you one-on-one coaching to answer your questions, clear your doubts, and keep you on track.

– To sharpen your career path, you will receive interview preparation tips, career coaching sessions, and resume revisions.

– The course duration is three months if you put 10 hours a week into learning. But you can choose those 10 hours according to your schedule.

– Get resource suggestions and constructive feedback from your mentors and the global learning community.

Duration: 3 months

Rating: 4.6 out of 5

You can Sign up Here

Review: This course has taught me a lot of things that are essential for a Machine learning Engineer – Arief R.

2. Post Graduate Certificate Program in AI and Machine Learning by Purdue University (Simplilearn)

This proactive program is designed to help you gain a strong understanding of the Python programming language and its libraries, writing scripts with the Jupyter-based lab environment , and much more. It is ideally prepared for business professionals with programming knowledge to help them learn essential AI and ML concepts like NLP, statistics, reinforcement learning, and deep learning. During the video lectures, you'll learn about deep learning concepts to build artificial neural networks and cross layers of data extraction while knowing about TensorFlow and Keras. Moreover, you'll get access to additional elective courses to expand your skills in subjects like NLP, GitHub Learning, Reinforcement Learning, etc. Check out our curation of Best Machine Learning Courses.

Key USPs –

– Offered in collaboration with Purdue University and IBM to offer a seamless and friendly learning experience from industry experts

– Gain knowledge of various AI-based technologies, such as ML, Deep Learning, NLP, Speech Recognition, etc.

– Provides a practical understanding of AI and ML algorithms to produce the best outcomes via Simplilearn's intensive Bootcamp learning model

– Enroll yourself in interactive learning models and live sessions by industry leaders, global practitioners, and industry projects

– Receive a professional PS Degree in AI and ML from the comfort of your home with flexible learning

Duration: 12 months, 5-10 hours/week

Rating: 4.5 out of 5

You can Sign up Here

Review: I'll give it a five-star rating…I enrolled in Data Science with Python course…the course content, shared drive, documents, pdf files, and — most importantly, the trainer — all are awesome. If you want to explore and gain knowledge, for sure go for Simplilearn. – Sneha Patil

3. Designing and Building AI Products and Services (MIT xPRO)

Created by professional instructors of MIT professional education, this executive program can help you understand design principles and applications of AI across various industries. Enrolling in this subjective prospectus will provide you with market-ready skills to evaluate the opportunity for AI solutions and making a case for it. You'll get acquainted with all the stages of AI-based products with a focus on specifics, such as the cost metrics and technical requirements of an AI software development plan. During the learning sessions, you'll get various deep learning topics, such as neural networks, artificial neurons, and the simulation of complex networks.

Key USPs –

– A suitable program included with various learning outcomes to help you become a design professional in AI and ML

– Gain knowledge about machine learning fundamentals while exploring the basics of deep learning and designing intelligent human-computer interactions

– Know how to define an appropriate level of machine involvement in interactions with humans and computers

– Learn to analyze how humans and machines can work together to surpass the sum of their parts while applying cognitive processes to various organizations

– Be an expert in designing and constructing a summary of an AI product or process with different learning modules

Duration: 8 weeks, 6 hours/week

Rating: 4.6 out of 5

You can Sign up Here

4. AI Applications for Growth (Kellogg School of Management)

If you want to gain comprehensive knowledge and skills in artificial intelligence to grow your business and build intelligent applications, this program is a great choice. Delivered by Kellogg School of Management's experienced faculty, this curriculum will help you learn how to apply an AI initiative while addressing critical business challenges related to AI technologies . It is specifically designed for senior technology managers, consultants, and senior managers to help them achieve a strategic perspective on AI to innovate operational processes. It comprises eight learning modules that will take you through a learning journey to understand various aspects of AI, like Business Support Functions, Transforming your Business, and Operations Management. Have a look at our compilation of Best Data Engineering Courses.

Key USPs –

– Learn to build a solid playbook for mount AI initiatives, determine the most impactful business problems, and drive responsible outcomes

– Learn how to drive marketing outcomes and advance your organization's transformation initiatives with data, analytics, and AI

– Gain a broad understanding of customer experience DNA framework to determine AI use cases for the customer journey

– Understand how AI can be used to optimize your assets and operating processes to improve agility, reduce operating costs, and improve safety

– Get access to live faculty teaching sessions and real-world applications for a better understanding

Duration: 2 months, 4-6 hours/week

Rating: 4.5 out of 5

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Review: The verticalization blueprint brought a lot of value and gave us real tools we can use in our organization. – Sanjeev Sethi

5. Applied Machine Learning Certificate Program by Purdue University (Simplilearn)

Ideally prepared for business leaders, IT consultants, and experienced developers, this practical curriculum will help you gain competitive knowledge of machine learning concepts. Signing up for this program will take you through a deep dive into real-world machine learning applications . You'll cover and learn essential data science and machine learning concepts, such as data analytics, wrangling, Python, feature engineering, statistics, supervised and unsupervised learning, and ensemble learning. You'll learn about the basics of Python programming, data operations, shell scripting, conditional statements, and Django framework . Moreover, you'll get access to 8X higher live interaction with hours of live online classes by industry experts.

Key USPs –

– A structured curriculum organized to help you gain adequate knowledge of machine learning algorithms from industry experts and skilled tutors

– Cover multiple AI and ML topics like feature engineering, feature selection, time series modeling, recommendation systems, and decision tree

– Offered in collaboration with the Purdue University and IBM to provide the best learning experience

– Offers additional Alumni association membership with the Simplilearn job assistance program to help you get your dream job

– Work with hands-on exercises and projects in integrated labs with real-time data from multiple domains

Duration: 6 months, 8 hours/week

Rating: 4.5 out of 5

You can Sign up Here

Review: The curriculum was well organized, covering all the root concepts and relevant real-time experience. The trainer was well equipped to solve all the doubts during the training. Cloud lab facility and materials provided were on point. – Vignesh

6. Machine Learning: From Data to Decisions (MIT Professional Education)

This introductory course is developed to help you gain knowledge about the machine learning tools and practices used to make informed decisions in critical situations. It comprises eight learning modules that focus on simplifying various aspects of machine learning like understanding the data models, classification, regression models, neural networks, and more. Signing up for this virtual program will help you learn about the basic geographies of data sets and identify practical statistical tools and visualizations to glean insights from the data. The course is organized with a step-by-step learning technique to provide you a comprehensive experience from scratch. After the course conclusion, you'll be able to make better business decisions by collecting data.

Key USPs –

– Get introduced to multiple aspects of machine learning, such as data modeling, data collection, and business decision making

– Understand the fundamental aspects of linear regression and how it can be utilized with collected data to develop models that can predict future outcomes

– Learn how classification is used to predict outcomes that fall under various categories like red, blue, green, yes, no, etc.

– Improve your understanding with real-world examples, case studies, and capstone projects provided to gain real-world experience of various industries

Duration: 8 weeks, 6-8 hours/week

Rating: 4.6 out of 5

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Review: The program had a great balance of theoretical explanations and live examples…showing a more systematic way of analyzing problems. – Navaneethan Krishnan

7. Become a Machine Learning Engineer for MS Azure (Udacity)

Individuals willing to improve their machine learning skills and develop practical experience can take help from this nano degree program offered by Udacity. In this course, you'll gain valuable experience in machine learning by training, validating, and evaluating models with Azure machine learning . It comprises three learning modules, including Azure Machine Learning, Machine Learning Operations, and a Capstone project at the end of the curriculum. Completing these modules will allow you to learn how to build and deploy sophisticated machine learning solutions with open-source tools and frameworks. Moreover, it is a flexible learning program that can be completed from anywhere at your convenience.

Key USPs –

– A comprehensive course designed to help you gain practical knowledge about machine learning algorithms and MS Azure

– Learn to install and configure machine learning pipelines in Azure while identifying essential use cases for automated machine learning

– Learn how to use Azure ML SDK for designing, creating, and managing machine learning pipelines in Azure

– Cover various concepts of operationalizing machine learning, such as selecting the suitable targets for deploying models, enabling application insights, and more

– Work your learnings via a capstone project to use your knowledge for solving an interesting real-world problem

Duration: 3 months, 5-10 hours/week

Rating: 4.7 out of 5

You can Sign up Here

8. Machine Learning Course by Stanford University (Coursera)

Coursera offers this Machine Learning course by Stanford University. The instructor of this course, Andrew Ng, is an adjunct professor at Stanford University, and the co-founder of Coursera as well. In this course, Andrew teaches the foundation of Machine Learning, Statistical Pattern Recognition, Data Analysis, and Datamining. As the outcome of enrolling in this course, you will learn the practical techniques of Machine Learning, and how to implement them to get things done. The course will not only give you a theoretical overview but also help you in learning through practical applications.

Key USPs –

– Learn the best innovations and practices of Machine Learning and Artificial Intelligence in Silicon Valley.

– Followed by several case studies and implementations, this course lets you apply your algorithm learnings to build smart robots.

– Learn the Linear Regression, its applications, and the Gradient Descent learning method.

– Learn Linear Algebra, Logistic Regression, Regularization, Neural Networks, Machine Learning System Designing, Support Vector Machines, Unsupervised Learning, Dimensionality Reduction, Anomaly Detection, Recommender Systems, etc.

– This course facilitates 56 hours of video lessons in the English language, and course completion certificate issued at the end of the course.

Duration: Self-paced

Rating: 4.9 out of 5

You can Sign up Here

Review: It was a great learning experience. All the lectures were in details. – Nikhil J

9. Machine Learning Engineering Courses (edX)

edX offers a plethora of exclusive Machine Learning and Artificial Intelligence courses. In this list of Machine Learning courses compiled by the experts of edX, they have included real college courses from MIT, Harvard, Microsoft, IBM, Caltech, Columbia, and other major universities. These courses are carefully designed to provide you with the right skills that will help you to pursue a lucrative tech career. Whether you are a Machine Learning beginner or want to hone your tech skills to a new level, edX has courses for all your needs. You will also get the option of trying a course before you pay for it.

Key USPs –

– Learn the data science essentials like Machine Learning and R with real-world case studies and Machine Learning Math essentials.

– Get to know the concepts of Data Science, Python, Artificial Intelligence, Data Analytics, Data Structure, Automotive Technologies, Natural Language Processing, Reinforcement, Speech Recognition, etc.

– Learn the use of Machine Learning applications, its tools, techniques, and how to publish a report after completing a project.

– Learn to design and develop intelligent agents using Artificial Intelligence to solve real-world challenges.

– Learn to program robots to perform real-time physical tasks.

– You can consume the course contents as per your convenience.

Duration: Self-paced

Rating: 4.5 out of 5

You can Sign up Here

10. Machine Learning (Stanford Online)

Artificial Intelligence is the future of Technology. And when it comes to technological studies, Stanford stands tall with is high-end study programs. The online Machine Learning program offered by Stanford School of Engineering teaches you the fundamentals of Artificial Intelligence, Machine Learning, and Data Science. The instructors of this program are industry leaders who have immense experience in efficiently communicating complex tech concepts. The enrolment option opens every quarter, and you need to complete your Non-Degree Option application to be considered for enrolment. It would be best if you are a Computer Science student to join this course. Having basic programming knowledge in Java, Python, and C++ is also a prerequisite. This course is beneficial for Software Engineers, Mathematicians, Statisticians, Analytics Professionals, Data Miners, Market Researchers, Predictive Modelers, and other related professionals.

Key USPs –

– Explore the useful applications of Data Science and Machine Learning to design and develop machine algorithms.

– Learn the fundamentals of Supervised Learning, Unsupervised Learning, Deep Learning, Learning Theory, and Reinforcement Learning.

– Learn to create computer systems for autonomous navigation, data mining, Artificial Intelligence probabilistic models, knowledge representation, robotic control, and other exciting tools.

– Learn to extract information easily from massive databases like large document repositories, social-network graphs, large websites, etc.

Duration: Self-paced

Rating: 4.5 out of 5

You can Sign up Here

So, these were the best Machine Learning Engineering Courses, Classes, Tutorials, Training, and Certification programs available online. Cheers to your success, Team Digital Defynd!