Which is the best machine learning course?

Machine Learning is the top domain in computer science these days. It is one of the evolving technologies with many organizations in different sectors. This technology can be beneficial for professionals working in various sectors. So, if you’re a professional seeking online courses for machine learning, many platforms provide the material.

You can get to know the basics of Machine Learning from these online portals and then implement these concepts in projects. These courses can help you get a new job or switch careers, or want to learn something new.

Please find some of the best machine learning course provider portals below:

1. Machine Learning by Stanford University

This is one of the most well-known Machine Learning courses available on the web. This course is taught by Andrew Ng, the former Chief Scientist for Baidu and Director of the Google Brain Deep Learning Project. You can learn both the theoretical aspects of Machine Learning algorithms and the practical implementations of it with the help of this course. Moreover, this course provides a full set of Linear Regression with One & Multiple Variable, Logistic Regression, Regularization, Neural Networks, Support Vector Machines, Unsupervised Learning, and many more implementing Octave or MATLAB. It takes about 11 weeks to complete this course, and it covers various aspects and applications of Machine Learning. These learning algorithms can help computer vision, database mining, text-understanding, designing robots, and several other applications. Upon completing this course, you receive a Shareable Certificate that you can attach to your resume or LinkedIn profile.

2. Deep Learning Specialization by DeepLearningAI

Deep Learning Specialization is an advanced specialization course by Andrew NG. You can go for this course after successful completion of the basic Machine Learning course. This course covers various aspects such as Convolutional Networks, Recurrent neural networks, Long short-term memory (LSTM), Natural Language Processing, and numerous others. Moreover, this course also provides personal stories and career advice from many top leaders in Deep Learning, which will enhance your experience. Deep Learning specialization offers five times comprising Neural Networks & Deep Learning, Improving Deep Neural Networks, Structuring Machine Learning Projects, Convolutional Neural Networks, and Sequence Models. This stream helps you create deep learning models in different fields such as autonomous driving, healthcare, natural language processing, music generation, and many more. Once you complete each of these courses successfully in specialization, you will receive a Shareable Certificate.

3. Machine Learning with Python by IBM

Machine Learning with Python teaches the applications of Machine Learning and its applications in the real world using Python. After learning the basics of machine learning, you can move on to its algorithms, such as Regression, Classification, and Clustering algorithms. The course is further classified into six weeks, with each of them targetting on an Introduction to Machine Learning, Regression algorithms including Linear, Non-linear, Simple, and Multiple regression, Classification algorithms including  SVM, Decision Trees, KNN, Logistic Regression, and more. Moreover, the clustering algorithms comprises of Hierarchical Clustering, Partitioned-based Clustering, and Density-based Clustering, Recommender Systems, and the final week inclusive of the Final Project that would implement everything you have learned.

4. Machine Learning by HarvardX

This course provides knowledge about the basics of Machine Learning and its various learning algorithms,v principal component analysis, and regularization by developing a movie recommender system. It also provides knowledge about data analysis and training data to receive useful insights. This course majorly focuses on ML algorithms like Linear Regression with One Variable, Linear Regression with Multiple Variables, Logistic Regression, Support Vector Machines, Unsupervised Learning, and a few others. Along with all the ML algorithms, it also teaches you cross-validation to avoid overtraining that data. You can prevail in an instructor-signed certificate from edX, and HarvardX is demonstrating your knowledge of Machine Learning for Data Science and analytics on successful completion of the course.

5. Principles of Machine Learning by Microsoft

This course covers basic principles of Machine Learning that are taught using theory and then followed by practical experiences. These experiences are made by creating and deploying ML models. You can use Python and Azure Notebooks to design these models and procure data insights. Furthermore, this course offers an introduction to Machine Learning and introduces you with data exploration, data preparation, Machine Learning algorithms. These algorithms comprise Supervised & Unsupervised Learning and improving model performance. Same as above, you would receive an instructor-attested certificate from edX and Microsoft to demonstrate your knowledge of Machine Learning for Data Science and Analytics at the end of the course.

All the courses mentioned above offer the best machine learning courses from basic to advanced levels.

From sales, marketing, accounting to distribution, customer management and operations - the application of Machine Learning (ML) can be witnessed in every industry you can think of today. And it is no surprise that it has become one of the most prominent career choices for students and professionals worldwide. As per Indeed, the best job of 2019 was Machine Learning Engineer with a 304% growth and an average base salary of $146,085/year.

Such staggering data and demand have made people rethink their career choice and pursue machine learning. It is a subfield of artificial intelligence (AI) where you learn to feed quality data to machines and then train them to process those data and algorithms to cultivate machine learning models. For example – chatbots, spam filtering, search engines, fraud detection, ad serving, fraud detection, social media listening and many more.

If you are a student then you can join a full-time course, and if you are a professional then you can choose courses from renowned professionals, companies and universities on Coursera, Udemy, edX etc.

Here are some of the most sought-after courses: 

Machine Learning by Harvard University (edX)

With the in-depth fundamental topics of Machine Learning, this course also covers algorithms – linear regression with one or multiple variables, logistics regression, unsupervised learning, predictive analysis and more. It teaches you cross-validation and helps you cultivate movie recommender engines as well. It is an 8-week duration course.

Advanced machine learning specialization (Coursera)

Designed by National Research University Higher School of Economics, this extensive course offers teaching on multiple techniques of machine learning. It helps you understand deep learning, visualization, neural networks, natural language processing, reinforcement learning and more. It is for professionals who have prior knowledge of linear algebra, statistics and calculus and want to gain expertise on the subject. The cost of this programme is $49/month.

Artificial Intelligence and Machine Learning Fundamentals (Udemy)

If you wish to solve real-world issues faced by companies/projects in real-time with predictive analysis and forecasting insights then this course is for you. It is framed keeping data scientists and developers in view who wish to add to their skillset and make improvements in the machine learning projects. You need to have a strong base in mathematics and Python programming language to sign up for this course. The enrolment charge of this course is $199.99.

Final words

These courses can open more opportunities for you in the field of data science and computer science. Do your research, compare the options and select the best one from them to reinforce your knowledge base.