During shopping online in any e-commerce website or maybe while booking a movie ticket through your mobile app, you might have noticed some recommendations shown to you every now and then, to help you purchase a certain product or to watch a particular movie, by the website or by the mobile app.

Do you know how is this possible? Which technology is responsible for providing these recommendations? If your guess is Machine Learning, then you are right. Because in today’s tech era, Machine Learning is emerging as one of the most powerful technologies, and is revolutionizing most of the sectors of this world.

Many applications such as chatbots and search engines are powered by this technology and are helping the organizations to serve their customers better than before. Machine Learning is a technology that enables the systems to automatically learn and improve from past experience without being explicitly programmed. It involves a process wherein you need not write any program or code to provide instructions to the computer to what to do, but instead provide a set of data, based upon which machines build their own logic and provide a better solution.

Looking at all the development taking place in this technology, we are here presenting a list of online courses on Machine Learning that have been presented by Simpliv, an online education platform, which we believe can be of great help for the people who are aspiring to learn and master Machine Learning technology.

These comprehensive courses have been designed considering all the industry requirements and help the students to successfully update their skills and stay ahead in the competition. These courses have been prepared by well-known authors from across the world, who have immense experience of working in this field and have in-depth knowledge of this technology.

So, let us now discuss about the 22 best online courses for Machine Learning [2020].

1. Machine Learning And Training Neural Network In MATLAB

Machine Learning is considered as a subset of Artificial Intelligence. Today, many people are willing to learn and become a master of Machine Learning technology. The course material provided by authors is good enough to effectively teach you Machine Learning and Artificial Neural Networks. It helps you to know how you can implement a simple Machine Learning Model in MATLAB.

Who can opt for this course: This course is for anyone interested in learning basic concepts of Machine Learning and Neural Networks.

Key takeaways:

• This course has been designed for students who are at the beginner level and for those who are interested in implementing Machine Learning in MATLAB.
• No prior technical knowledge will be required for taking up this course. However, if candidates have the knowledge of MATLAB, that can be an added advantage.
• Undertaking this course will help the candidates to understand Machine Learning and also know how they can train a simple Model in MATLAB on a simple Dataset.

Course features:

• Duration of the course: 01 hour, 30 Minutes
• Number of Lectures: 6
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

2. DATA SCIENCE With MACHINE LEARNING And DATA ANALYTICS

If you are looking to learn Data Science in simple and easy steps using R programming, Python programming, WEKA tool kit, and SQL, then this course is best suited for you. All the lectures included in this comprehensive Data Science course cover complete Data Science life cycle concepts such as Data Collection, Data extraction, Data Cleansing, Data Exploration, etc.

Some of the tools and skills that are covered as part of this course are as follows:

• Statistical Analysis
• Text Mining
• Regression Modelling
• Hypothesis Testing
• Predictive Analytics
• Machine Learning
• Deep Learning.

Programming languages like R programming, Python are covered extensively as part of this Data Science training.

Who can opt for this course:  Graduates from any stream can opt for this course.

Key Take-aways:

• Basic mathematical knowledge (probability and statistics), basic SQL queries and basic programming knowledge is enough.
• This course will help you to learn Data Science with Machine Learning and Data Analytics using R, Python, WEKA, and SQL.

Course features:

• Duration of the course: 72 hours, 23 minutes
• Number of lectures: 86
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

3. Practical Deep Learning: Image Search Engine

This course has been designed to help you to stay competitive in the AI job market by teaching you how to create a Deep Learning End-to-End product on your own. This is a unique course that helps you to learn how to write a whole End-to-End pipeline, from data pre-processing across choosing the right hyper-parameters, to showing your users’ results in a browser.

This is a perfect course for people who haven’t worked together on the image to image search engine, starting from ground zero – image pre-processing, creating a model, training it, then testing. After learning these, you learn to create a simple web application and use it to serve our model in production.

Key Take-aways:

• This course will help you to understand to build your AI based Image-to-Image search engine
• This course will help to create an End-to-End pipeline for any Deep Learning model using Tensorflow.

Course features:

• Duration of the course: 01 hour, 33 minutes
• Number of lectures: 25
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

4 . Learn Artificial Intelligence For Beginners

Are you a beginner and willing to learn Artificial Intelligence? Then, this is the right course for you to learn this technology. This course focuses completely on teaching the fundamental concept of AI. All the lectures included in this course are so well taught that they help you to understand the concept very easily.

Who can opt for this course: Anyone who wants to learn Artificial Intelligence can take this course.

Key Take-aways:

• This course helps the candidates to understand some of the important aspects about Artificial Intelligence such as the definition of AI, applications of AI, etc.
• This course will allow you to understand what is Machine Learning, different types of Machine Learning, etc.

Course features:

• Duration of the course: 01 hour, 08 minutes
• Number of lectures: 21
• Language: English.
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sing up for this course here.

5. Machine Learning And Data Science Using Python For Beginners

Artificial Intelligence, Machine Learning, and Deep Learning are among the most discussed terms of the present IT industry. This course focuses on teaching mainly Machine Learning and Data Science concepts to beginners using Python programming language with libraries such as Scikit-learn, SciPy, Matplotlib & Pandas.

Some of the topics this course will cover are:

Who can opt for this course: Anyone who wants to learn Machine Learning and Data Science using Python programming language can opt for this course. This course is of great use to beginners who want to learn these technologies.

Key Take-aways:

• This course provides you in-depth knowledge about various concepts of Machine Learning and Data Science using Python programming language with Scikit-learn, SciPy, Matplotlib & Pandas.

Course features:

• Duration of the course: 10 hours, 19 minutes
• Number of lectures: 90
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

6. Machine Learning Using R And Python

Both R and Python are prominent programming languages used extensively for developing Machine Learning projects. Learning these programming languages can be very useful for professionals. So, this course has been designed to help such professionals who want to learn Machine Learning using R and Python.

This course has been prepared for such professionals who are aspiring to learn the basics of R and Python and develop applications involving Machine Learning techniques such as recommendation, classification, regression, and clustering.

Who can opt for this course: All graduates can opt for this course. Before anyone takes up this course, they should have prior knowledge of R packages and Python, Numpy, pandas, SciPy, matplotlib, Windows and any Linux operating system flavors.

Key Take-aways:

• This course will help you to learn to solve data-driven problems and implement your solutions using the powerful, yet simple programming languages R and Python with its packages
• This course will help you to gain a broad picture of the Machine Learning environment and the best practices for Machine Learning techniques.

Course features:

• Duration of the course: 69 hours, 42 minutes
• Number of lectures: 83
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

7. Machine Learning Adv: Support Vector Machines (SVM) In R

Are you looking for a complete Support Vector Machines course that teaches you everything you need to create Support Vector Machines in R? Then, this is the ideal course for you. This course will teach you some of the advanced techniques of Machine Learning, which are Support Vector Machines. It covers all the steps that one could take while solving a business through Decision tree.

Who can opt for this course: This course is for people who are pursuing a career in Data Science. Anyone looking to master SVM techniques from beginner to advanced, in a short span of time can opt for this course.

Key Take-aways

• This course will allow you to get a solid understanding of Support Vector Machines
• Through this course, you will understand the business scenarios where Support Vector Machines is applicable.

Course features:

• Duration of the course: 03 hours, 04 minutes
• Number of lectures: 26
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

8. Machine Learning Adv: Support Vector Machines (SVM) Python

If you are looking for complete knowledge about  Support Vector Machines, then, you are on the right platform. This course teaches you everything that you need to create a Support Vector Machines model in Python.

Through this course, you will be able to learn some of the advanced techniques of Machine Learning, which are Support Vector Machines. This course covers all the steps that one needs to take to solve a business problem through the Decision tree.

Who can opt for this course: This course is for people who are pursuing a career in Data Science. Anyone curious to understand and master SVM techniques from Beginner to Advanced in a short span of time can opt for this course.

Key Take-aways

• This course is designed to help you understand Support Vector Machines
• Through this course, you will be able to tune a Machine Learning model’s hyperparameters and evaluate its performance.

Course features:

• Duration of the course: 03 hours, 59 minutes
• Number of lectures: 33
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.  

9. Amazon Alexa 101: Publishing Alexa Skills Without Coding!

If you are all willing to learn how to develop skills without coding for Amazon’s Alexa, then this course is best suited for you.

As many companies are willing to add Alexa voice control to their products and services, it has given rise to the demand for Alexa Skill Developers. If anyone wishes to learn this skill, then it is the perfect time for them. One of the best things about this course is that it covers almost all features of Alexa Skills with real-world example skills (including a published skill).

Who can opt for this course:

Key Take-aways

• This course will help the students to create their own custom skills for Amazon Echo Services
• This will help them in Monitoring and Data analysis for your Alexa App
• It helps them in creating and storing user input in variables
• It helps them to create a basic conversation between Amazon Alexa and a user.

Course features:

• Duration of the course: 02 hours, 07 minutes
• Number of lectures: 15
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

10. Road Map To Artificial Intelligence And Machine Learning

Are you looking to pursue a career in Artificial Intelligence and Machine Learning, and have questions like:

• What are the prerequisites for learning AI?
• What is the roadmap to start the Machine Learning project (ML)?

Then take up this course to find an answer for all such queries.

Even if you don’t have any basic programming knowledge, you can understand Artificial Intelligence and Machine Learning in-depth by signing up for this course. The course has been designed based on maximum queries searched in Google or posted in  AI forums.

Who can opt for this course: Anyone who wants to learn Artificial Intelligence and Machine Learning technologies can take up this course.

Key Take-aways:

• This course will help the candidates to know how to choose the best programming language for AI
• Candidates will know how much mathematical knowledge is needed for AI
• Candidates will understand different types of Machine Learning algorithms and real time scenario examples.

Course features:

• Duration of the course: 54 minutes
• Number of lectures: 7
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

11. Machine Learning Using Python: Learn Hands-On

Python is one of the most widely accepted programming languages among Machine Learning professionals for working on various projects. This language plays an important role in the adoption of Machine Learning in the business environment.

Some of the topics covered as part of this course are:

• Linear Algebra
• Exploratory Data Analysis
• Linear Regression
• Various Classification techniques
• Clustering
• Dimensionality reduction
• Artificial Neural Networks

Who can opt for this course: The course has been designed for students who are pursuing Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, Economics or any engineering field.

Key takeaways:

• This course help students learn Linear Regression, SVR, Decision Tree Regression, Random Forest Regression
• This course also helps students to learn Supervised Learning & Unsupervised Learning.

Course features:

• Duration of the course: 07 hours, 07 minutes
• Number of Lectures: 48
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

12. Artificial Intelligence In FinTech

Machine Learning has made a huge impact on the financial industry. This is one of the premium courses for someone interested in learning about the application of AI and ML in the financial services industries. All the lectures have been so well taught that at the end of the course, you will be familiar with basic concepts of ML and AI, and will appreciate how they are being used in the financial services industry.

Who can opt for this course: This course is for anyone who is interested in learning about Machine Learning and Artificial Intelligence in FinTech.

Key takeaways:

• The course help the candidates to learn the basic concepts related to Data Science, Machine Learning and Artificial Intelligence
• The course provides a closer look at several ML and AI financial services use cases (B2B and B2C).

Course features:

• Duration of the course: 01 hour, 36 minutes
• Number of lectures: 8
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

13. Data Preprocessing For Machine Learning Using MATLAB

This course comes with a practical oriented approach. In this course, all the coding will be done in MATLAB, which is one of the fundamental programming languages for engineers and science students and is frequently used by top Data Science research groups worldwide.

Some of the topics covered during this course are:

• Introduction to course and MATLAB
• Handling Missing Values
• Dealing with Categorical Variables
• Outlier Detection
• Feature Scaling and Data Discretization
• Selecting Techniques for your Dataset.

Key takeaways:

• This course helps the candidates to learn Machine Learning for Data Science using MATLAB
• It helps the students to learn Advance MATLAB Data Types and Data structures.

Course features:

• Duration of the course:  04 hours, 13 minutes
• Number of lectures: 30
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

14. Machine Learning In The Cloud With Azure Machine Learning

This course is all about discussing Azure Machine Learning in detail. The lectures included in this course will help you to learn what features it provides and how it is used. Here, you will learn how to process some real-world datasets and find some patterns in that dataset.

The course teaches you how to design, deploy, configure and manage your Machine Learning models with Azure Machine Learning. This course begins with an introduction to the Azure ML toolset and features provided by it and then focus on building some machine learning models based on some real-world problems.

Who can opt for this course: This course is for everyone who are looking to learn Machine Learning in the cloud with Azure Machine Learning.

Key takeaways:

• It helps you to build and run a Machine Learning experiment with real-world datasets
• Here you can learn how to use classification Machine Learning algorithms.

Course features:

• Duration of the course: 02 hours, 55 minutes
• Number of lectures: 36
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

15. Machine Learning With AWS

This course helps the candidates to learn and practice all the services of AWS Machine Learning which is offered by AWS Cloud. One of the best things about this course is that it provides both theoretical and practical sections of each AWS Machine Learning Services.

Who can take up this course: This course is best suited for those who are looking to learn Machine Learning with AWS.

Key takeaways:

• This course allows you to learn various machine learning algorithms supported by Azure Machine Learning
• It helps you to build and run a Machine Learning experiment with real-world datasets
• Here you can learn how to use classification Machine Learning algorithms.

Course features:

• Duration of the course: 03 hours, 22 minutes
• Number of lectures: 42
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

16. Machine Learning Python: Regression Modelling

The is one of the best courses for those who are curious about learning Machine Learning. This course aims to educate you about all the steps of creating a Linear Regression model, which is the most popular Machine Learning model, to solve business problems.

The lectures in the course help you to understand:

• How to do a preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression.
• How to interpret the result of the Linear Regression Model and translate them into actionable insight
• The basics of statistics and concepts of Machine Learning
• Advanced variations of the OLS method of Linear Regression
• Linear Regression technique of Machine Learning using Scikit Learn and Stats model libraries of Python.

Who can take up this course: This course is for everyone who wants to master the basics of Machine Learning skills.

Key takeaways:

• The course helps to understand how to interpret the result of a Linear Regression model and translate them into actionable insight
• Understand the basics of statistics and concepts of Machine Learning.

Course features:

• Duration of the course: 07 hours, 13 minutes
• Number of lectures: 51
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

17. Learn By Example: Statistics And Data Science In R

This course is an introduction to Data Science, Statistics and R using real-life examples. All the lectures included in this course are very well designed and each of the concepts is explained with the help of examples, case studies and source code in R wherever necessary.

You need not require a prior quantitative or mathematics background to take up this course. It starts by introducing the basic concepts such as the mean, median, etc. and eventually covers all aspects of an Analytics (or) Data Science career from analyzing and preparing raw data to visualizing your findings.

Who can opt for this course: This course is best suited for MBA graduates or business professionals who are looking to move to a heavily quantitative role. This course can be taken by engineers who want to understand basic statistics and lay a foundation for a career in Data Science.

This course is best suited for Analytics professionals who have mostly worked in Descriptive Analytics and want to make the shift to being modelers or Data Scientists.

Key takeaways:

• This course helps you understand linear regression and use it confidently and use it to build models
• The course teaches you to use Linear regression in R to overcome the difficulties of LINEST() in Excel.

Course features:

• Duration of the course: 09 hours, 07 minutes
• Number of lectures: 82
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

18. Complete IOS 11 Machine Learning Masterclass

If you are looking to learn how to start building professional, career-boosting mobile apps and use Machine Learning to take things to the next level, then this course can be very beneficial to you. This course helps to create 7 projects from scratch in practical code-along tutorials. Here, you can also learn to integrate live video camera stream object recognition to your apps.

In this course, you can learn to create your own custom models.

Who can opt for this course: This course is best for people with a basic foundation in iOS programming who would like to discover Machine Learning, a branch of Artificial Intelligence.

This course is also helpful for people who want to pursue a career in combining app development and Machine Learning to become a hybrid iOS developer and ML expert.

Key takeaways:

• The course has been well designed to help you to understand the tools and techniques of Machine Learning for iOS on an instinctive level
• Here you will learn to convert ML models to iOS ready models.

Course features:

• Duration of the course: 01 hour, 08 minutes
• Number of lectures: 4
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

19. Introduction to Data Science With R

This is the course that has been specially designed to introduce the R programming environment as a way to have hands-on experience with Data Science. Initially, the course starts with a few examples in R before moving onto doing statistical processing, and then the course introduces Machine Learning with techniques such as regression, classification, clustering, and density estimation, in order to solve various data problems.          

Who can opt for this course: The course is for the professionals who want to learn Data Science with R programming language.

Key takeaways:

• Here you will learn to write simple R programs to do basic mathematical and logical operations
• This course will help you to learn loading structured data in R environment for processing.

Course features:

• Duration of the course: 01 hour, 08 minutes
• Number of lectures: 4
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

20. Statistical Modeling For Data Science

Adapting to technological changes is a very important aspect in today’s modern world. It is always recommended for IT professionals to keep updating their knowledge to stay ahead of the competition. This course teaches you to learn statistical modeling for Data Science.

Who can opt for this course: Any professional who wants to learn Statistical modeling for Data Science can opt for this course.

Key takeaways: This course will  teach you all the important aspects about statistical modeling for Data Science and help you build a career in Data Science.

Course features:

• Duration of the course: 01 hour, 04 minutes
• Number of lectures: 13
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

21. Machine Learning From Scratch Through Python

This is one of the platforms to learn Artificial Intelligence, specially Machine Learning and also Deep Learning as well. This course is for beginners. If candidates have basic knowledge of Python, then it can be helpful for them to understand the concepts easily. The authors make sure that this course is always updated with all the new happenings in this field of technology.

Who can opt for this course: Any profession who want to learn Machine Learning from scratch through python can take up this course.

Key takeaways:

• This course helps you to build your own Machine Learning and Deep Learning algorithms.  

Course features:

• Duration of the course: 12 hours, 15 minutes
• Number of lectures: 14
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up for this course here.

22. Python For Data Science

This is a wonderful platform for you to learn Data Science and Machine learning from scratch. All the lectures included in this course teach you the concept very well and provide you in-depth knowledge about the subject. In the course, the author has covered everything from “Hello World” in Python to all the required libraries like Pandas and Numpy.

Who can opt for this course: Any professionals who are interested to learn Data Science and Machine Learning can take up this course.

Key takeaways:

• Through this course, you will get to learn everything in Python that is required for Data Science, Machine Learning and Deep Learning
• This is a great tutorial to get started with the topic as you are not required to have any prior knowledge. Everything will be taught from scratch.

Course features:

• Duration of the course: 02 hours, 45 minutes
• Number of lectures: 21
• Language: English
• Course type: Self-paced, online
• Access on Android and iOS App: Yes.

You can sign up this course here.

Conclusion:

We believe that here we have given the best collection of online courses on Machine Learning to our readers. The primary purpose of this blog is to help people find all the best courses on Machine Learning under one umbrella. We hope this blog has been successful in achieving its goal.

We want to know what our readers have to say about this blog. Please send your feedback in the comment section. We also request you to share this blog among your network so that it reaches to the maximum people and help someone who is looking for such a list of courses on Machine Learning.