15 Best Machine Learning Courses [MIT | Stanford | Kellogg] [2024 April]

Team DigitalDefynd

Ready to dive into the future? Welcome to the vibrant world of machine learning – a field reshaping our technological landscape. In this exciting domain, machines evolve to make predictions and decisions based on patterns, much like the human brain. It’s a space where innovation meets intelligence, offering a golden opportunity for those eager to spearhead advancements in the tech industry. Embarking on a learning journey in machine learning isn’t just an enhancement of your skills; it’s a gateway to a promising and dynamic career.

To kickstart this exhilarating journey, you’ve landed at the right spot! At DigitalDefynd, we’ve utilized our expertise to bring you the finest machine-learning courses. Our curated list encompasses free and premium courses, catering to a wide spectrum of learners, from novices to seasoned professionals. As you sift through this carefully assembled selection, you’ll encounter courses that offer a harmonious blend of theoretical knowledge and practical application, promising an enriching and enjoyable learning experience. We encourage you to delve into these courses, each designed to guide you step-by-step toward mastery in the machine learning field. So far, 165,000+ students and professionals have benefited from it. Gear up for this educational adventure, where opportunities and groundbreaking discoveries await you! You should also have a look at Best Artificial Intelligence Executive Education Programs.

15 Best Machine Learning Courses for 2024

Machine Learning in Business (MIT Executive Education)

Managers and business executives who want to gain a decisive competitive edge in their business with machine learning can take help from this course. This is a short online program created by experienced faculty members of MIT University to help you discover the potential of machine learning so that you can develop strategies for effective implementation. Although the course is designed for leaders and decision-makers, any individual interested in gaining a grounding knowledge in machine learning can take this course. Once you finish the course with the final assignments, you will get a certificate of completion from MIT Sloan.

Highlights –

– A comprehensive program that focuses on the managerial implications of machine learning and some technical aspects to provide better knowledge to craft an effective machine learning strategy.

– Get exposure to the technical elements of machine learning that will enable you to leverage the technology without any coding and programming knowledge.

– Walkthrough the weekly modules of the course to learn how you can shape an applied integration strategy for implementing machine learning and its business applications.

– Get the liberty to prepare yourself from the comfort of your home with flexible deadlines.

Duration: 6 weeks, 6-8 hours/week

Rating: 4.5 out of 5

You can Sign up Here

Machine Learning Specialization by Stanford & DeepLearning.AI (Coursera)

The Machine Learning Specialization is an online program created for beginners in collaboration between DeepLearning.AI and Stanford Online. It will teach you the basics of machine learning and techniques to build real-world AI applications. Andrew Ng, who has led critical research at Stanford University and worked at companies like Google Brain, Baidu, and Landing, will be teaching this program. The specialization comprises three courses. These are Supervised Machine Learning: Regression and Classification, Advanced Learning Algorithms, Unsupervised Learning, and Recommenders, Reinforcement Learning.

Key USPs –

– Earn a shareable certificate upon completion.

– This specialization is delivered 100% online.

– You can start instantly and learn at your own pace.

– You can set the schedule on your own.

– It is ideal for beginners.

– Learn to build ML models with NumPy & scikit-learn.

– Understand how to create supervised models for prediction & binary classification tasks (linear, logistic regression).

– Learn to apply best practices for ML development and use unsupervised learning techniques.

– Learn how to build a neural network with TensorFlow.

Duration: approximately 2 months

Rating: 5 out of 5

You can Sign Up Here

Review- Very useful! Prof. Andrew Ng is absolutely a great educator. – JH

Machine Learning Course A-Z™: Hands-On Python & R In Data Science (Udemy)

Let us just begin by absorbing the fact that 411,800+ students have taken this course and it has an average rating of 4.5 out of 5. We consider this as one of the Best Machine Learning Course and it is developed by Kirill Eremenko, Data Scientist & Forex Systems Expert and Hadelin de Ponteves, Data Scientist.

This course will help you Master Machine Learning on Python and R, make accurate predictions, build a great intuition of many machine learning models, handle specific tools like reinforcement learning, NLP and Deep Learning. Most importantly it teaches you to choose the right model for each type of problem. Basic high school mathematics is all you are supposed to know to take up this course. With 40 hours of learning + 19 articles, we don’t know what else we should say to make you check this out. Do check out our compilation of Python Data Science Courses.

Highlights –

– Great tutorial to get started with the topic with little or no prior experience.

– Explore complex topics such as natural language processing, reinforcement learning, deep learning among many others.

– Tons of practical exercises and quizzes to measure your grasp on the concepts covered in the lectures.

– Detailed instructions are provided to install the required software and tools.

– As a bonus, this training contains both Python and R code template that can be downloaded and used in projects.

Duration: 41 hours

Rating: 4.5 out of 5.

You can Sign up here

Review – Machine Learning A-Z is a great introduction to ML. A big tour through a lot of algorithms making the student more familiar with scikit-learn and few other packages. The theoretical explanation is elementary, so are the practical examples. ML A-Z is a right course for a beginner to get the motivation to dive deep in ML. From here you can choose where to go and, therefore, master it! In short, very introductory, no-brainer, wide coverage. A good way to start. -Denis Mariano

Post Graduate AI Machine Learning Certificate Program (Purdue University)

This postgraduate program is an excellent option if you want to advance your knowledge and experience in artificial intelligence. Enrolling in this post-graduation program will help you learn and understand various technologies and aspects of AI and ML, such as Python, Statistics, Deep Learning Networks, and Reinforcement learning. The curriculum is designed by an expert faculty of Purdue University, who have trained multiple individuals in artificial intelligence. You will receive continuous support and assistance from the instructors throughout the classes to help you cope with AI’s core concepts. After concluding the program, you’ll also receive job assistance from the Simplilearn job assistance program to help you get your dream job.

Highlights –

– An excellent curriculum prepared to help you unlock your potential as an AI professional and ML expert.

– Learn about multiple AI-based technologies, such as machine learning, deep learning, natural language processing, computer vision, speech recognition, etc.

– Cover multiple classes during the video sessions like Data Science with Python, Deep Learning with TensorFlow and Keras, and more.

– Gain knowledge of multiple tools uses in AI and ML, including Flask, Matplotlib, Python, Amazon SageMaker, Django, and NLTK.

Duration: 12 months, 5-10 hours/week

Rating: 4.6 out of 5

You can Sign up Here

Professional Certificate in Machine Learning and Artificial Intelligence (Berkeley Engineering)

If you are an IT and engineering professional who wants to reveal new opportunities for your career growth or create an innovative career path, this six-month online course is the right choice. Joining this online program will provide you with all the critical knowledge and practical applications of AI/ML tools and frameworks required to convert into an exciting, high-demand career in this field. Throughout the comprehensive curriculum, you will cover three main sections: Foundations of AI/ML, AI/ML techniques, Advanced topics, and Capstone projects. In addition, you will be able to build a market-ready GitHub portfolio after course completion to show it to prospective employers.

Highlights –

– A perfect program to learn and understand ML and AI concepts and identify the best machine learning models to fit different business situations

– Know how to implement the ML/data science life cycle and devise innovative solutions to real-life issues within your organizations

– Gain a verified digital certificate of completion from UC Berkeley Executive Education to advance your skills and career growth

– Get practical, hands-on experience using advanced AI/ML tools to succeed in this fast-paced field

Duration: 15-20 hours

Rating: 4.8 out of 5

You can Sign up Here

Designing and Building AI Products and Services (MIT xPRO)

This productive curriculum is designed to help you understand AI’s designing aspects and applications across various industries. In this curriculum, you’ll learn how to develop an AI-based product proposal and represent it to your internal stakeholders and investors. You’ll learn about various stages involved in AI-based product designing, the fundamentals of the machine and deep learning algorithms, and applying your insights to solve practical problems. You’ll get to work with real-life examples and industry case studies to understand concepts better. After finishing the program, you’ll understand how deploying the right AI technologies in your organization can help you automate routine tasks and engage with customers.

Highlights –

– Ideally designed for technical product managers, technology professionals, founders, and UI/UX designers involved in managing user experience of AI-based applications

– Broaden your understanding of developing AI-based solutions with machine learning algorithms and design technology solutions

– Explore multiple designing processes involved in AI-based products while expanding your knowledge in calculus, statistics, linear algebra, and probabilities

– Be able to differentiate between various machine learning algorithms, design AI products to solve organizational issues, and apply machine learning methods to practical problems

Duration: 8 weeks, 6 hours/week

Rating: 4.6 out of 5

You can Sign up Here

AI Applications for Growth (Kellogg School of Management)

With this AI Strategy course, you can expect to learn the best possible ways to practically use Artificial Intelligence for automating your business process. If you are an AI career aspirant or want to adopt AI in your business, then this course is one of the best resources available to get started. Learn to drive unbeatable AI strategies for 20+ industries (including Finance, Healthcare, and Automobile) by leveraging AI frameworks like AI Canvas, AI Radar, and AI Capability Maturity Model. The creators of this course, Mohanbir Sawhney, and Varun Poddar are globally recognized AI innovators known for their tremendous contribution to several tech giant companies.

Highlights –

– Learn to use AI in creative ways by going through the 50 use cases across different industries.

– Get real-world application experience by working in Data Labs with real-world Data Sets.

– The course is perfect for mid-career professionals, senior-level executives, and investors.

– After completing this course, you will get a verified course completion certificate if you pass with 80% marks.

Duration: 2 Months/ 4-6 hours per week

Rating: 4.5 out of 5

You can Sign up Here

Free Course Trial – Deep Learning Course (deeplearning.ai)

One of the most renowned instructors of Deep Learning, Andrew Ng brings to you this special course developed in association with Stanford Professors and NVIDIA|deep learning institute as industry partners. The trainer is the Co-Founder of Coursera and has headed the Google Brain Project and Baidu AI group in the past.

In this program spread across 5 courses spanning a few weeks, he will teach you about the foundations of Deep Learning, how to build neural networks and how to build machine learning projects. Most importantly, you will get to work on real-time case studies around healthcare, music generation and natural language processing among other industry areas. More than 250,000 students have already enrolled in this program from all over the globe. Without a doubt, this is the Best Deep Learning Course out there. You may also be interested in having a look at our compilation of the Best Data Science Courses as well as Best Python Course.

Highlights-

– Learn about convolutional networks, RNNs, BatchNorm, Dropout and more.

– Different techniques using which you can build models to solve real-life problems.

– Real-world case studies in fields such as healthcare, autonomous driving, sign language reading, music generation, and natural language processing are covered.

– Gain best practices and advice from industry experts and leaders.

– Complete all the assessments and assignments as per your schedule to earn the specialization completion certification.

Duration: 3 months, 11 hours per week

Rating: 4.9 out of 5

You can Sign up Here

Review : This course formed a concrete background in building multi-layers neural network from scratch. The best advantage of this course is I was able to immediately apply the knowledge I gained into real world problem like humanoid navigation towards known targets. Illustration is great in terms of mathematical explanation and coding in a step by step walk through. – Waleed E

Professional Certificate in Machine Learning and Artificial Intelligence (Imperial College)

If you are interested in becoming a part of the innovative field with high-growth potential to impact the world positively, this online program can help you in your quest. In this 25-week online learning course, you will learn from a unique combination of advanced technical expertise and business awareness to give you a competitive edge. It will also help you navigate your job search to find exciting career opportunities in ML and AI. Throughout this comprehensive curriculum, you will cover several learning modules, including evaluating predictive performance, statistics for machine learning, and advanced topics in performance evaluation. In the end, you will get associate alumni status from Imperial College London on program completion.

Key USPs –

– Find the underlying elements of convolutional neural networks and finally practice the skills required for real-world model optimizations in your capstone project

– Explore how decision trees can be leveraged to classify or predict outcomes and solve real-world problems

– Be able to build and refine machine learning models using Python and industry-standard tools to measure and improve performance

– Understand basic and advanced concepts and trends in artificial intelligence, as well as potential real-world implications

Duration: 25 weeks

Rating: 4.7 out of 5

You can Sign up Here

Artificial Intelligence: Business Strategies and Applications (Berkeley Exec Edu)

If you want to obtain a solid understanding of AI technologies to grow your business, this program from Berkeley Executive Education is an excellent option. Enrolling in this practical session will help you gain a thorough impression of modern technologies, including limitations and capabilities, while understanding AI, its methods, and business applications. You’ll learn how to organize and optimize compelling AI application projects while avoiding pitfalls associated with new technologies. Besides, you’ll gain a solid understanding of the most preferred ways of transitioning from traditional machine learning to deep neural networks learning and its typical applications. Upon finishing the associated courses, you’ll receive a certificate of completion to share with employers. If you are interested in artificial intelligence, do remember to check out the best AI Courses as compiled by experts on our website.

Highlights –

– Obtain a solid understanding of various AI technologies like machine learning basics, neural networks, deep learning, robotics, and AI strategy development

– Learn to grasp the technical aspects of AI to communicate effectively with technical teams and colleagues

– Get the opportunity to learn from industry experts and guest speakers who will address the significant issues faced while implementing AI in an organization

– Obtain a complete understanding of how machines see and talk, computer vision, and natural language processing

Duration: 2 months, 4-6 hours/week

Rating: 4.5 out of 5

You can Sign up Here

Free Course Trial – Mathematics for Machine Learning and Data Science Specialization (Coursera)

Mathematics is the foundation of machine learning and data science technologies. This course helps you learn some important math topics, such as machine learning calculus, probability, statistics, and linear algebra. It is for beginners who want to specialize in these topics and prepare for a career as a data professional. Understand the math behind machine learning algorithms. Employers expect some fundamental math skills in their data professionals.

The program helps you understand how math is used in machine learning. It also has interview questions to help you get your dream job. Learn to analyze data using statistical techniques. Represent data in the forms of matrices and vectors. Identify data properties with the help of linear independence, rank, and singularity concepts. DeepLearning.AI brings to you this education program that teaches you the mathematics at the core of machine learning technology.

Highlights:

– A machine learning education program focused on its mathematical aspects

– Learn the math skills that make you an ML expert

– Use of innovative mathematics pedagogy that makes learning quick and easy

– The course has intuitive plug-ins and visualization models

-Suitable for students who understand mathematics of high school level

Duration; 3 months

Rating: 4.6 out of 5

You can Sign up Here

Free Course Trial – Mathematics for Machine Learning Course by Imperial College London (Coursera)

It is safe to say that machine learning is literally everywhere today. Many of us take numerous courses to learn the various concepts in these topics but unfortunately, one of the crucial parts of this field is often overlooked. This specialization aims to bridge that gap and helps you to build a solid foundation in the underlying mathematics, its intuitive understanding and use it in the context of machine learning and data science. Start with Linear Algebra and Multivariate Calculus before moving on to more complex concepts. By the end of the classes, you will have a strong mathematical footing to take more advanced lessons in ML and become a professional.

Highlights-

– Fundamental concepts show you how to use them on huge pools of information.

– The lectures include a detailed explanation of how to get started with the graded assignments.

– The third course is of intermediate level and requires basic Python and numpy knowledge.

– Optimize fitting functions to get good fits to data.

– The doubts are clarified to provide a clear understanding of mathematics and apply it to necessary problems.

Duration: 2 months, 12 hours per week

Rating: 4.6 out of 5

You can Sign up Here

Review : This course brilliantly delivered on each of its intended learning objectives in an engaging and non-threatening way – I would encourage anyone interested in this topic, regardless of their background. The course instructors are excellent, and the forum discussions are extremely helpful if/when you are ever stuck. – Daniel G

Applied Machine Learning (Columbia Engineering Executive Education)

If you have an intermediate acquaintance of Python, and you are willing to expand your knowledge in Machine Learning, then this course from Columbia Engineering is an excellent choice for you. In this course, you will learn a wide variety of techniques of supervised and unsupervised machine learning approaches with Python programming language. The trail follows a practical approach that invites participants into a conversation, where you will learn with live subject matter experts. After completing this course, you will be equipped with a standard knowledge of Applied Machine Learning that can be implemented in various industries, such as Healthcare, Retailing, Software Development, etc.

Highlights –

– Get introduced to the fundamental concepts of data science, such as working with different data types and operations in Python, writing functions in Python, data manipulation and analysis, data visualization, and much more

– Learn about various regression models, such as linear regression, least squares, regularization, as well as Bayesian methods like MAP inference, Bayes rule, Active learning, etc.

– Get a solid understanding of foundational classification algorithms like Nearest Neighbors, Logistic Regression, Refinements to Classification, Kernel methods, and many more

– Get certified in applied machine learning with a certificate of completion after finishing the course

Duration: 5 months, 8-10 hours/week

Rating: 4.6 out of 5

You can Sign up Here

Review: The course does not only give a comprehensive overview and the most useful tools to apply machine learning in practice, but it also provides the underlying mathematics to understand what’s behind the magic.” — Willem Romanus

Machine Learning, Data Science and Deep Learning with Python (Udemy)

This tutorial by Frank Kane is designed for individuals with prior experience in coding and offers all the training required to go for top-earning job profiles in this field. The lectures focus on the practical applications of the algorithms instead of the technical jargon. Explore how to use tools for visualization, image recognition, mine datasets, test and train models to name a few. By the end of the program, you will be familiar with the techniques and methods that are listed by data science and machine learning employers.

Highlights-

– Installation steps are provided for all the major operating systems.

– Numerous optional lectures and activities are available for additional learning.

– Lessons are followed by regular exercises that let you practice the concepts.

– Experiments and projects that show how ML can be useful in solving challenges.

– Hands-on examples are available for reference.

– Draw from the experience of the instructor and incorporate them into your habit.

– 101 Lectures + 5 Articles + Full lifetime access

– Work with different scales of data and build solutions.

– Register at a nominal price.

Duration: 13 hours

Rating: 4.5 out of 5

You can Sign up here

Review : I really liked the high-level overview. The material presented was “really a lot”, and I feel it just touched the surface. I think that this course can be easily broken down to more detailed couple of courses with more exercises like the “Final Project”. Frank, well-done; I hope that one day I will have the privilege of shaking hands with you. – Ramy Taraboulsi CEO, VeritableSoft Innovations Inc.

Free Machine Learning Course (fast.ai)

This is one of the top platforms that provide courses on topics that come under artificial intelligence and is created with the aim to teach the masses about AI and how to get started in the field. All the content is covered from scratch and focuses on learning by doing. There are a series of choices available for both beginners and experienced learners. So if you are serious about getting started in this area then the easiest way is to click on the first lecture.

Highlights-

– Each and every concept is covered with screenshots and hands-on examples.

– Complete guidance is provided to perform the configuration to get started with the lectures.

– Join the forum to communicate with peers and practitioners and help each other through the learning experience.

– Use the fast.ai library and train models.

– All the courses on this platform are available for free.

Duration: Self-paced

Rating: 4.5 out of 5

You can Sign up Here

Related: Top AI Terms Defined

AWS Machine Learning Nanodegree Program (Udacity)

This Udacity Nanodegree Program that will help you gain the must-have skills for all aspiring data analysts and data scientists. Explore the end to end process of investigating data through a machine learning lens. Learn to extract and identify useful features that can be used to represent your data in the best form. In addition to this, you will also go over some of the most important ML algorithms and evaluate their performance.

Highlights-

– Interactive quizzes allow you to brush up the topics covered.

– Join the student support community to exchange ideas and clarify doubts.

– The self-paced schedules allow you to learn at your convenience.

– The content has been created in association with Kaggle and AWS

– You will learn about supervised learning, deep learning, unsupervised learning among a host of other topics

– You also get a one on one mentor, personal career coaching along with access to the student community

Duration: 3 months

Rating: 4.6 out of 5

Intro to Machine Learning with PyTorch Nanodegree Program (Udacity)

This nano degree program is prepared to teach you the foundational machine learning techniques, including data manipulation, supervised, and unsupervised algorithms. It is ideally prepared for students who have experience in Python and want to expand their knowledge in other subjects of machine learning. The curriculum is designed in collaboration with Kaggle and AWS, which means you’ll be learning from the best instructors in the world. During the video sessions, you’ll also get access to real-world projects from industry experts, technical mentor support, and career services that are additionally offered to help you improve your learning experience.

Highlights –

– A comprehensive program designed to help you get introduced to the fundamental concepts of Machin Learning with PyTorch

– Explore the deep and unsupervised learning algorithms of machine learning while getting practical experience of applying your skills to code exercises and projects

– Know about the practicalities of neural network design and training in PyTorch while learning a standard class of methods for model construction

– Learn to implement unsupervised learning methods for different problem domains

– Get continuous support from knowledgeable mentors to guide you throughout your learning process and answer your questions

Duration: 3 days, 10 hours/week

Rating: 4.8 out of 5

Review: I’ve taken a lot of online courses in Data Science/Machine Learning over the last year, and I wish I had started here. A lot of courses just focus on teaching material with no application, but I’ve already learned more in this course than most of the others combined. Learning the essentials and then implementing them in the projects with feedback from real people, I’d say it’s as good if not better than my current college program. – Derek H.

Intro to Machine Learning with TensorFlow Nanodegree Program (Udacity)

This is another excellent course on Udacity designed to teach you the basics of machine learning with TensorFlow. In this program, you’ll learn the foundational machine learning algorithms from scratch, including data cleaning, supervised, and unsupervised models. Later on, you’ll get to explore some advanced concepts like deep and unsupervised learning with the practical implementation of coding skills to real-world projects. This curriculum is ideal for individuals who have experience in Python and want to further take their machine learning skills. After finishing this nano degree program, you’ll receive a certificate of completion to share with employers and your LinkedIn profile.

Highlights –

– Learn about the foundational machine learning algorithms from data manipulation to unsupervised and supervised algorithms in TensorFlow and Scikit-learn

– Know about the standard class of methods for model construction with supervised learning

– Work your skills with real-world projects and immersive content that is organized in partnership with top-tier companies to master the tech skills

– Get the custom learning plan tailored to fit your convenience and need with the freedom to study at your own pace

– Avail experienced career services from experts to help you get the best job in the machine learning field

Duration: 3 months, 10 hours/week

Rating: 4.7 out of 5

Review: It’s going slower than I expected but that’s just that – wrong expectations. Covered a lot of materials. Most of exercises are good but I would like to see more industry applications for the topics covered. While it is expected a student will be doing some research on their own a list of resources would save time. Overall, I like the way courses are structured. Good job Udacity! – Vadim M.

Python for Everybody (University of Michigan)

This specialization will introduce you to the foundational programming concepts including data structures, networked application program interfaces, and databases using Python. After the completion of all the core concepts, you will get the opportunity to work on a final project and design and create your own applications for data retrieval, processing, and visualization.

Highlights-

– Perfect for learners with little or no basic programming experience.

– Implement the concepts covered in the lessons by writing your first Python program and experimenting with the different techniques.

– The lectures are designed in a fun and interactive manner which makes it engaging and intriguing.

– The program is divided into a series of 5 courses with an increasing level of difficulty.

– Create applications for data retrieval and processing.

– Understand the basics of SQL and database design.

Duration: 3 months, 11 hours per week

Rating: 4.8 out of 5

Review : I love the teaching style of Dr. Severance!! I’ve tried so many other tutorials online but his class is by far my favorite. He helps cement connections by use of metaphors and visual aids and as a student who has traditionally favored subjects such as language arts, it has been invaluable to my learning experience!! – Lorilyn M

Deep Learning A-Z™: Hands-On Artificial Neural Networks (Udemy)

Created by Kirill Eremenko and Hadelin de Ponteves, this is one of the Best Deep Learning Course that you will find out there. It will help you understand the intuition behind Artificial Neural Networks, Recurrent Neural Networks, Self Organizing Maps, Boltzmann Machines, Auto Encoders and teach you how to apply them.

This course is carefully designed to give you the full experience of working in this technology from scratch. The lectures don’t only cover the techniques of solutions to the problem but it also describes the importance of the techniques and how it actually makes a difference. Along with the classes, you will get the chance to work on exciting projects with real-world datasets. With over 120,000 students, this training is certainly a crowd favorite.

Highlights –

– These lectures can be taken by individuals with any level of experience in this field.

– Understand the intuition behind the recurrent and convolutional network, Boltzmann machines and apply them in practice.

– Write the codes from scratch in every practical tutorial with guidance from the instructor.

– All the codes are available for download and can be used in projects.

– Work on six real-life challenges with updated datasets.

– Learn to work with some of the most popular open-source tools such as Tensorflow, Pytorch among others.

– 187 Lectures + Full lifetime access + 32 Articles

Duration: 22.5 hours

Rating: 4.5 out of 5

Review : This is the third course i concluded with Kirill and Hadelin, the experience is always very pleasant with a lot of content and things to learn. This specific course brings lavish recommendation articles and texts so you can go deeper into the more complex supervised and unsupervised algorithms. For me, always an A+. – Leandro Coriolano

Free Machine Learning Course with R (DataCamp)

If you are well versed in R programming and statistics and want to build upon that skill then this is interactive course is worth a look. Firstly you will look into the applications and common problems that can be solved using this area. In addition to this, you will focus on the three basic techniques, and train and assess ML models. On completing the journey you can go for more advanced specialization.

Highlights-

– Compare the different types of algorithms and experiment with them.

– Categorize data, build a decision tree, perform clustering and more.

– 15 Videos + 81 Exercises

– Interactive content makes the explanation simpler and learning a fun experience.

– The first module is available for a free preview.

Duration: 6 hours

Rating: 4.4 out of 5

Master of Science of Machine Learning (Imperial College London)

Earnings a master’s degree in computer science can be beneficial in bagging research and development, or engineering-based jobs in the advanced technologies. This program created by Imperial College London is one of the first to offer an opportunity to earn a master’s degree online. The classes not only show you how to build systems for predictions, classification of information but also gain practical knowledge of solving problems faced in the real world. You will also hone your analytical skills, explore the subject from an ethical point of view and look into the relevant tools like PySpark.

Highlights-

– Contribute insights drawn from the developed systems to make strategic decisions that affect your organization.

– Top researchers and instructors guide you throughout the process of earning a degree.

– Pass the assessments and coursework with a score above the cutoff to complete the program.

– Projects and thesis in collaboration with top technology-based companies.

– Answer a few questions and get feedback on whether this course is the right choice for you.

Duration: Self-paced

Rating: 4.5 out of 5

Advanced Machine Learning Course by HSE (Coursera)

This certification course has been developed by a team of 21 lecturers, professors and researchers; and it is an advanced level journey into the world of ML. Only those with basic or intermediate knowledge around the subject should enroll for this one. You will be taught about natural language understanding, reinforcement learning, computer vision, and Bayesian methods. Some of the trainers for this program include Pavel Shvechikov, Researcher at HSE and Sberbank AI Lab, Anna Kozlova, Team Lead; Evgeny Sokolov, Senior Lecturer; Alexey Artemov, Senior Lecturer and Sergey Yudin, Analyst-developer among multiple other trainers. If you have a strong understanding of the machine learning concepts and are proficient in solving relevant challenges, then this specialization will help you to go a notch higher.

Highlights-

– Get introduced to advanced topics such as deep learning, reinforcement learning, natural language processing, computer vision and more.

– The lessons are designed concisely which helps you to learn new skills in a short amount of time as well as enhance your portfolio.

– Assignments give you an opportunity to implement the knowledge covered in the lessons.

– Work on projects and learn about the experiences of top CERN scientists and Kaggle machine learning practitioners.

Duration: Flexible Schedule

Rating: 4.6 out of 5

Data Science and Machine Learning Bootcamp with R

If all the previous courses concentrated on Python, this one is about R. With over 100 lectures and detailed code notebooks, this is one of the most comprehensive courses for machine learning and data science. One of the best parts of the course is its instructor. Jose Marcial Portilla, has a BS and MS in Engineering from Santa Clara University and has been working as a professional instructor and trainer for Data Science & programming for many years now. No matter whether you are a beginner or an experienced programmer looking for an opportunity to make a switch to a data scientist or ML engineer profile then this is the course for you. Using one of the most popular languages, R you will study decision trees, handle data from different sources, scrap web among important topics and techniques. In addition to this, you will also utilize R to create visualizations and models.

Highlights-

– Little or no prerequisite is required for enrollment.

– Analyze and implement different machine learning algorithms.

– Assignments with a gradually increasing difficulty level.

– 127 Lectures + 8 Articles + 3 Downloadable resources + Full lifetime access

– Work on practical projects that give you a chance to apply knowledge gained from the lectures.

Duration: 17.5 hours

Rating: 4.7 out of 5

Review : This course is great because it puts you in more challenging situation which are, from the other side, feasible and it gives you sense of learning. A lot of very useful materials, good foundations, good for systematising basic concepts. Very good exercises, challenging but well adjusted that you will not lose self-confidence. It gives you good basis for further learning and very good literature to master machine learning. -Vitomir Jovanović

Professional Certificate in Data Science by Harvard University (edX)

This Harvard University professional certification program uses motivating case studies, asks specific questions and shows you how to answer them by analyzing huge amounts of data. Throughout the classes, you will simultaneously learn the R programming language, statistical concepts, and data analysis techniques. The case studies covered include World Health and Economics Trends, US Crime Rates, the Financial Crisis of 2007-2008, election Forecasting, Building a Baseball Team and Movie Recommendation Systems. The professor of this course is Rafael Irizarry, a Professor of Biostatistics at Harvard University.

Highlights –

– Cover the fundamental R programming skills.

– Explore statistical concepts such as probability, inference, and modeling and apply them in practice.

– Gain experience with the tidyverse, including data visualization with ggplot2 and data wrangling with dplyr.

– Become familiar with essential tools for practicing data scientists such as Unix/Linux, git and GitHub, and RStudio.

– Implement machine learning algorithms and gain in-depth knowledge of this area with real-life case studies.

Duration: 9 courses, 2 to 8 weeks per course, 2 to 4 hours per week, per course

Rating: 4.7 out of 5

Free Machine Learning Courses (edX)

edX brings together a host of courses on machine learning from a variety of colleges across the globe. You can choose to study Data Science from Harvard, Artificial Intelligence from Columbia, Python Data Science from IBM or Data Science from Microsoft among a host of other courses. Most of these programs are free to audit, and you only need to pay if you wish to enroll for a certificate. With timings ranging from a few weeks to a few months, there’s something for everyone in these courses.

Highlights –

– Free courses for those not wanting to shell out big bucks to learn machine learning

– Explore the various topics of machine learning and artificial intelligence and gain a strong understanding

– Learn with an abundant amount of tips and tricks from the instructors

– Build complex data models, explore data classifications, regression and clustering and more.

– Numerous courses to choose from covering a range of topics from AI to Machine Learning, Deep Learning and more

– Top professors from leading universities teach you

Duration: Self-paced

Rating: 4.6 out of 5

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

Course has been discontinued

Participants will gain a practical understanding of the tools and techniques used in machine learning applications. In the MIT tradition, you will learn by doing. There are no prerequisites in terms of math or computational science, although basic understanding of statistics is helpful. This is not a coding course, but rather an introduction to the many ways that machine learning tools and techniques can help make better decisions in a variety of situations.

Highlights-

– On your journey to learning MIT Professional Education’s Machine Learning: From Data to Decisions online program, you’ll be in good company. Past participants come from a wide range of industries, job functions, and management levels.

– This online program requires no prerequisites in terms of math or computational sciences, although some experience with introductory-level statistics is helpful.

– This online program takes a look at machine learning through a lens of practical applications. It is designed specifically for professionals who want to develop a competitive edge by turning what is unknown into what’s known-leading to better decisions and outcomes.

– Faculty: Devavrat Shah is a professor with the department of electrical engineering and computer science at MIT.

– Certificate: Get recognized! Upon successful completion of the program, MIT Professional Education grants a certificate of completion to participants.

Duration: 8 weeks

Rating: 4.8 out of 5