A team of 50+ global experts has done in-depth research to come up with this compilation of Best + Free Machine Learning Courses for 2020. All these courses are available online and will help you learn and excel at Machine Learning. These are suitable for beginners, intermediate learners as well as experts. This compilation is reviewed and updated monthly. So far, 149,000+ students and professionals have benefited from it.

8 Best Machine Learning Courses for 2020

This is undoubtedly the best machine learning course on the internet. Created by Andrew Ng, Co-Founder of Coursera and Professor at Stanford University, the program has been attended by more than 2,600,000 students & professionals globally, who have given it an average rating of a whopping 4.9 out of 5. One look at the testimonials and you will know why we so highly recommend it.

The topics covered in the course include supervised learning, best practices, and innovation in ML and AI, while you also get to encounter numerous case studies and applications among a host of other things. One of the best parts about the course is that you can enrol for a 7 day trial before going on to purchase the entire class. If you were to take our word for it, this is hands down the best program for the subject available online. You may also be interested in taking a look at a compilation of some of the best Machine Learning Certification.

Key USPs-

– Understand parametric and non-parametric algorithms, clustering, dimensionality reduction, among other important topics.

– Gain best practices and advice from the instructor.

– Interact with your peers in a community of like-minded learners from all levels of experience.

– Real-world based case studies give you the opportunity to understand how problems are solved on a daily basis.

– The flexible deadline allows you to learn at your convenience.

– Learn to apply learning algorithms to build smart robots, understand text, audio, database mining.

Duration: Approx 55 hours, 7 hours per week

Rating: 4.9 out of 5

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Review : Truly an exceptional class. Not often will someone with a deep proficiency in a discipline have the time or incentive to share their insights and teach to others; this class is a rare exception, and given the vital importance of machine learning to the future, I have a great appreciation and debt to Andrew Ng. – Nicholas D

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.

Key USPs-

– 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

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Review : digitThis 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

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.

Key USPs –

– 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.

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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-az 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

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.

Key USPs-

– 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

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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

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.

Key USPs –

– 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

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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.

Key USPs-

– 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

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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.

Key USPs-

– 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

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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.

Key USPs –

– 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

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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

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.

Key USPs-

– 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

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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

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 learn the R programming language, statistical concepts, and data analysis techniques simultaneously. The case studies covered include Trends in World Health and Economics, 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.

Key USPs –

– 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

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This micro masters program designed by Columbia University brings you a rigorous, advanced, professional and graduate-level foundational class in AI and its subfields like machine learning, neural networks and more. With a total of 4 courses in this program go over the important concepts of this topic none by one. Gain a solid foundation of the guiding principles of AI and apply the knowledge of machine learning to real-world challenges and applications. Along with this, you will also learn to design neural networks and utilize them to work on relevant problems. By the end of the program, you will gain adequate practical knowledge to enhance your portfolio, apply to relevant job profiles or go freelance.

Key USPs-

– Apply the concepts of machine learning to real-life challenges and applications.

– Thorough instructions are provided for configuring and navigating through the required software.

– Working on designing and harnessing the capabilities of the neural network.

– The program is divided into 4 courses along with relevant examples and demonstrations.

– Apply the knowledge gained in these lectures in an array of fields such as robotics, vision and physical simulations.

Duration: 4 courses, 12 weeks per course, 8 to 10 hours per week, per course

Rating: 4.5 out of 5

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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. We also have a comprehensive collection of deep learning courses on the website.

Key USPs –

– 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

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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

Individuals who have basic knowledge of AI and machine learning, and want to take their expertise to the next level can take part in this post-graduate diploma program. This program is offered by Columbia University to help individuals learn and understand the core concepts of artificial intelligence and machine learning. There are three modules of this program, which includes Applied Machine Learning, Applied Artificial Intelligence, and a Capstone Project. During the program, you will get the opportunity to get in touch with the instructor in order to resolve and understand complex queries related to the course. Also, after completing the capstone project, you will get your diploma certificate from Columbia University.

Key USPs –

– Learn about supervised and unsupervised machine learning, which include topics like regression, clustering, sequential data models, and many more

– Get introduced to artificial intelligence and other essential concepts like Heuristic search, Logical agents, Adversarial search, etc.

– Enroll in live online teaching sessions provided by the instructor to help you better understand the subjects

– Get access to video lectures, quizzes, application assignments, discussions forms, and much more to improve your overall knowledge of the field

– Join a community of more than 7400 learners when you enroll in this diploma program

Duration: 9 months, 7-8 hours/week

Rating: 4.6 out of 5

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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.

Key USPs-

– 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

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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.

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.

Key USPs-

– 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

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Machine Learning Courses – Bonus

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. If you are interested in artificial intelligence, do remember to check out the best AI Courses as compiled by experts on our website.

Key USPs-

– 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

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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.

Key USPs-

– 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

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Review : This course is one of the most difficult I have seen but at the same time it is very well structured. Lectures are understandable, one just need some support from other materials to understand a whole content, at least for me. I struggled a bit with a final project but in general, I enjoyed it a lot, I looked forward to it each week, it was challenging and achievable. I recommend it. – Vratislav H

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.

Key USPs-

– 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

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Review : This course is great becease 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

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.

Key USPs-

– 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

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6 Free Machine Learning Courses for 2020

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.

Key USPs –

– 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

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Coursera has compiled a list of courses to upgrade your existing skills in this in-demand field. You can choose to commence from scratch or work on a particular aspect with choices like applied ML in Python, and foundations with a case study approach. Introduction to data and probability and Bayesian statistics are programs that provide you the prerequisite knowledge to keep up with the important topics. Lastly, you can also find online bachelor’s and master’s degrees from top academic institutions. We have also compiled a list of best Coursera Machine Learning Courses.

Key USPs-

– Take your pick from specializations, individual courses, professional and master track certificates, and degrees.

– Study anytime and anywhere with flexible schedules.

– Apply the acquired skills in the final project and hands-on exercises.

– 24X7 support is available to attend to your queries.

– Complex maths are broken down and explained at a great pace with demonstrations.

Duration: Self-paced

Rating: 4.5 out of 5

You can Sign up Here

Udemy offers 400 tutorials and certifications on machine learning and skills related to this field. In case you want a little help or recommendation for finding a suitable course for you then you can take the short quiz available on the platform. Hands-on Python & R In Data Science, ML Bootcamp, deep learning with Python, AWS SageMaker are some of the highest-rated classes on the platform. If you are looking for a program for putting your knowledge to practice then you have an option like practical real-world applications, TensorFlow 2.0, and deploying models. You may also want to have a look at Best Udemy Courses.

Key USPs-

– Lessons for beginners require little or no prior experience.

– Learn to predict future trends by varying the parameters of the analysis.

– Explore topics like NLP, reinforcement and deep learning.

– Identify the challenges and choose which model will be most efficient.

– Lectures + Articles + Downloadable resources + Full lifetime access

– Plenty of coding tutorials follow the videos.

Duration: Self-paced

Rating: 4.5 out of 5

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