Top 10 Machine Learning Courses

Introduction

 

Machine Learning has emerged as one of the most rapidly developing and advancing disciplines in the field of computer science, with applications spanning a wide range of industries. 

 

In 1959, Arthur Samuel, an American expert in the field of virtual reality and Artificial Intelligence, invented the phrase "Machine Learning" and defined it as "the field of study that provides machines the potential of acquiring knowledge on their own without being explicitly programmed."

 

Machine Learning has proven itself beneficial in numerous sectors, including social media, business analytics, traffic alerts, virtual assistants, transportation, product recommendations, and so on. There are many applications of machine learning.

 

Many individuals want to learn about this topic for projects or to pursue it as a profession because of its wide range of applications. There are several paid and free courses accessible online on various educational sites such as Udemy, Coursera, and others that teach the fundamentals of Machine Learning Algorithms. Some of these courses also offer certification upon completion, which may be a valuable addition to any résumé.

 

(Must check: Machine Learning Tutorial)

 

 

Machine Learning Courses

 

Given below are the top 10 Machine Learning Courses available online:

 

1. Machine Learning by Stanford University (Coursera)

 

Platform: Coursera

Completion Time: 61 hours (Approx.)

Enrollment fee: Free

Cost of Certificate: Rs. 4315 (INR)

Rating: 4.9/5

 

This course is offered by Stanford University through the Coursera platform and is taught by Andrew Ng, a Stanford University professor, co-founder of Coursera and Google Brain, and Vice President of Baidu. This course is suitable for beginners and covers the following topics:

 

• Parametric/Non-parametric Algorithms

• Neural Networks

• Linear Regression with One Variable/ multiple variables.

• Clustering

• Deep Learning

• Support Vector Machines

• Dimensionality Reduction

• Logistic Regression

• Recommender Systems

• Bias/Variance theory

 

This course also digs into numerous machine learning and deep learning applications, teaching students how to use various algorithms for text interpretation, database mining, audio, computer vision, tiny robotics, and so on.

 

(Recommended read: Top 7 text mining techniques)

 

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

 

Platform: Udemy

Completion Time: 45 hours(Approx.)

Cost of Course: Rs. 8640 (INR)

Rating: 4.5/5

 

The primary goal of this course is to develop Machine Learning Algorithms in the Python and R computer languages. Kirill Fremenko and Hadelin de Ponteves, two data science professionals, devised this course. The following topics are covered in this course:

 

• Data Preprocessing

• Regression

• Classification

• Clustering

• Association Rule Learning

• Reinforcement Learning

• Natural Language Processing

• Deep Learning

• Dimensionality Reduction

 

This course is designed for beginners and delves into the specifics of all of the subjects discussed above. Many implementations and real-life situations are covered, providing students with both practical and academic understanding. After finishing this course, students will be able to create strong machine learning models and apply them to find solutions.

 

(Must read: 5 Clustering Methods in Machine Learning)

 

3. Introduction to Machine Learning (Udacity)

 

Platform: Udacity

Completion Time: 10 weeks (Approx.)

Enrollment fee: Free

Cost of Certificate: Certificate not available

Rating: NA

 

This intermediate-level Machine Learning course by Sebastian Thurun and Katie Malone is designed for learners who are just getting started with Machine Learning. It is a module under Udacity's Data Analyst Nanodegree. Topics covered in this course:

 

• Naive Bayes

• Support Vector Machines

• Decision Trees

• Datasets

• Machine learning Algorithms

• Regression

• Outliers

• Clustering

• Feature Scaling

 

This course assists in the solution of practical issues as well as the analysis of data using Machine Learning techniques. The students enrolling in this course must have prerequisite knowledge of the Python programming language. Email inbox mining and financial data mining are two of the applications covered in this course.

 

4. Machine Learning with Python by IBM (Coursera)

 

Platform: Coursera

Completion Time: 21 hours (Approx.)

Enrollment fee: Free

Rating: 4.7/5

 

Python is a user-friendly and approachable programming language and this course aims to teach Machine Learning through Python. Offered by IBM and taught by Saeed Aghabozorgi and Joseph Santarcangelo, this course gives a general overview of Machine Learning and delves into its application in the real world. Topics covered by this course:

 

• Regression

• Classification

• Clustering

• Recommender Systems

 

All the above-mentioned subjects are discussed in detail and sub-topics like Linear, Non-linear, Simple, and Multiple Linear regression, Classification algorithms including  SVM, Decision Trees, KNN, Logistic Regression, etc. are explained. In the end, the students work on a final project, utilizing all the concepts.

 

5. Machine Learning Specialization by University of Washington (Coursera)

 

Platform: Coursera

Completion Time: 7 months (3 hours/week)

Enrollment fee: Free

Cost of Certificate: Rs. 3584 (INR) /month

Rating: 4.7/5

 

This is a specialization offered by Coursera for people who want to master Machine Learning. It contains four courses within itself:

 

• Case Study Approach

• Regression

• Classification

• Clustering and Retrieval

 

These courses cannot be accessed individually. Through this specialization, one will know Machine learning concepts, Data Clustering Algorithms, Python programming, Deep Learning, Logistic Regression, Classification Algorithms, Decision tree, Linear Regression, Regression analysis, and statistics. This specialization also provides an opportunity to work on projects and provides certificates on completion of the entire course.

 

6. Machine Learning for Data Science and Analytics (edX) 

 

Platform: edX

Completion Time: 5 weeks (7 hours/week)

Enrollment fee: Free to Audit

Cost of Certificate: Rs. 7386

Rating: NA

 

This is an introductory course offered by ColumbiaX through edX platform. It is intended to teach you the foundations of Machine Learning and its many algorithms. The topics discussed in this course are:

 

• Machine Learning algorithms

• Linear Regression

• Logistic Regression

• Support Vector Machines

• Unsupervised learning

 

This course is beneficial for people who are looking for practise along with theoretical knowledge. It contains many assignments within the course that will provide hands-on experience to the students. It also teaches data predictions by data analysis that uses topic modeling to search hidden meanings in huge amounts of data. This course provides a certificate on completion.

 

7. Data Science and Machine Learning Bootcamp with R (Udemy)

 

Platform: Udemy

Completion Time: 17.5 hours(Approx.)

Cost of Course: Rs. 8640 (INR)

Rating: 4.7/5

 

This Udemy course, created by Jose Portilla, seeks to educate data science and machine learning in the language R. It covers subjects such as data manipulation, data visualisation, data science, and data analysis, as well as managing CSV, Excel, SQL, and web scraping using R. The following topics are addressed:

 

• Data Science and Machine Learning 

• Introduction to R basics

• R Matrices

• Machine Learning with R

• Linear Regression

• K Nearest Neighbors

• K Means Clustering

• Decision Trees

• Random Forests

• Data Mining 

• Neural Nets and Deep Learning

• Support Vector Machines

• R data frames

• R lists

 

This is a beginner friendly course and provides a certificate on completion.

 

8. Bayesian Machine Learning in Python: A/B Testing (Udemy)

 

Platform: Udemy

Completion Time: 10.5 hours(Approx.)

Cost of Course: Rs. 8640 (INR)

Rating: 4.5/5

 

This course is created by Udemy Business and is concerned mainly about A/B testing. This machine learning course is beginner friendly and covers different topics of Data Science and Machine Learning and discusses different Data Analytics Techniques for Marketing, Digital Media, Online Advertising, etc. Some of the topics covered are:

 

• Bayesian Machine Learning

• Real-world examples of A/B testing

• Bayes rule

• Traditional A/B testing

• Bayesian A/B Testing

• Bayesian A/B Testing Extension

 

This is an intermediate level course and requires prerequisite knowledge of Python programming language. It covers Bayesian Machine learning and gives real life examples for application.

 

9. Unsupervised Machine Learning Hidden Markov Models in Python (Udemy)

 

Platform: Udemy

Completion Time: 9 hours(Approx.)

Cost of Course: Rs. 1920 (INR)

Rating: 4.7/5

 

This intermediate level Machine Learning course in Udemy is curated by Udemy Business collection and focuses mainly on Hidden Markov Models (HMM), which is an unsupervised learning sequence. The topics covered through this course are:

 

• Introduction to HMM

• Markov Models

• HMM for discrete observations

• Discrete HMMs using Deep Learning Libraries

• HMMs for continuous observations

• HMMs for Classification

• Parts of speech Tagging

• TensorFlow

 

This course offers many practical applications of Markov models and HMMs. It also teaches to analyze website interaction and fix problems like high bounce rate. Through this course, one will have required knowledge of NLP.

 

10. Intro to Machine Learning with PyTorch - Nanodegree program (Udacity)

 

Platform: Udacity

Completion Time: 3 months (10 hrs/week.)

Enrollment fee: Rs. 47,967 (INR)

Rating: 4.7/5

 

This is a nanodegree programme presented by Udacity in partnership with Kaggle and AWS to learn Machine Learning using Python. It is recommended that students have prior understanding of the Python programming language. This program's detailed coursework are as follows:

 

• Supervised Learning

• Deep Learning 

• Unsupervised Learning

 

This programme covers real-world machine learning applications by industrial professionals and teaches you how to extract and differentiate key highlights that can be used to talk to your data in the best way.

 

(Similar read: Top 8 AI course)

 

Conclusion

 

Machine learning has become a buzzword in the technological sectors as it has advanced in the field of Artificial Intelligence. Because of the availability of the Internet, it is now simpler for people to study Machine Learning through many online courses curated by industry professionals for minimum prices and apply the information in various projects or applications.