Machine learning has become the talk of the tech industry, disrupting traditional businesses with automation. With strong roots in statistics, it has become a core technology with the potential to impact all aspects of human life including personal, professional and the way we communicate with others. That’s one reason why industries and businesses are after machine learning software as a way to integrate the technology into their existing systems and processes.
From fraud detection to automated chatbots and from spam filtering to ad serving, machine learning is slowly redefining all aspects of everyday like. And that’s just the beginning, the tech that helps scientists build mathematical models or allow businesses to understand customers’ behavior pattern is none other than machine learning. In short, while most people may not notice, in reality, machine learning solutions have already taken over our daily lives and allowed us to do things that otherwise would be impossible to achieve.
But, what’s the best machine learning courses that can help you get started with the technology?
Well, in this blog, we have come up with some of thebest machine learning courses available online (free and paid). All machine learning programs listed below are chosen for quality and richness of content, as well as, customers’ reviews and ratings.
It is important to note that unlike data science courses that cover various subjects like communication, exploratory data analysis, visualization techniques, and others, machine learning courses are more rigidly limited to the development of algorithms, the mathematical working of algorithms and the ability to utilize them in a programming language.
So, let’s now start our list of best machine learning courses available online:
10 Best Machine learning Courses and Certifications Skills Programs for 2021
- Professional Certificate Program in Machine Learning and Artificial Intelligence
- Machine Learning with TensorFlow on Google Cloud Platform Specialization
- Machine Learning Stanford Online
- Professional Certificate in Foundations Of Data Science
- Certification of Professional Achievement in Data Sciences
- eCornell Machine Learning Certificate
- Certificate in Machine learning
- Harvard University Machine Learning
- Machine Learning with Python
- Machine Learning at Udacity
5 Top Free Machine Learning Online Courses and Certifications Skills Programs for 2021
- Free Machine Learning Course (fast.ai)
- Machine Learning Course by Stanford University (Coursera)
- Free Machine Learning – Artificial Intelligence Course (Columbia University)
- Free Machine Learning Introduction Course (Udacity)
- Free Machine Learning Data Science Course (Harvard University)
Pre-Criteria and Pre-Requisite Before Taking Up any Machine Learning Course/Program
Well, if you want to learn machine learning online, the first prerequisite is to choose a machine learning class that delivers quality content that’s strictly focused on the development and implementation of machine learning algorithms. Here I have come up with well-defined criteria that can help you choose the best machine learning programs online and develop your first machine learning algorithm.
The best online machine learning courses should:
- Firmly focused on development and implementation of machine learning algorithms
- Must use open-source language like Python, R Packages
- Must use open-source libraries of the programming languages (courses using commercial packages should be discarded altogether from consideration)
- Must be based on hands-on experience with programming assignments
- Explain the background mathematical working of algorithms
- Be executed at self-paced
- The instructors must deliver lectures in engaging ways
- The lectures should be interactive
- Have above average-rating for the program at forums and other aggregators
Now, once you apply all these filters, you will be left with some high-quality machine learning programs, which you can screen further to choose the best online course that’s worth your time and money.
To even fasten the pace of your learning the machine learning, you should read some comprehensive machine learning books, which will further strengthen your understanding of the technology and greatly boost your capacity to learn algorithm development.
Here we have come up with two great machine learning books, which you should check out before taking up online machine learning class.
This is an amazing book that brings much-needed clarity to the complex mathematical intuitions required for the development of machine learning algorithm development. The book is written in a straightforward approach and covers great details on the theory side of the things. Also, there are some exercises and examples to give a better understanding of using the R programming language.
This is yet another great machine learning book, which also nicely complements the previous book we discussed above. This book takes a more practical approach by detailing the application of machine learning using Python. This machine learning book together with some of the other books that are listed below will certainly help you to enhance your programming capacity for the development and applications of machine learning algorithms.
Best Books on ML and AI
Here are some other great books on artificial intelligence and machine learning; especially suited for beginners that will nicely complement the machine teaching class to build machine learning skills.
Any list for the best Artificial Intelligence and machine learning books will be incomplete without mentioning this book by the legendary Andrew Ng. The book has become one of the most popular and widely read books on machine learning and AI.
The book is written in a manner to help readers enhance their skills to create AI systems. Taking an interactive course, the book helps beginners to understand various factors that are needed to be taken into consideration for machine learning projects. Andrew Ng. is definitely by far the best author that you should read to start your progress towards AI and ML algorithm development.
The Hundred-Page Machine Learning Book
Author: Andriy Burkov
What makes this book unique is how easily the author has been able to bring clarity to the otherwise complex equations and masterfully summarize difficult topics in some 100-odd pages. The book is written succulently which opens up the complex theories and mathematical intuitions involved in machine learning for the easy understanding of beginners.
Programming Collective Intelligence (PCI)
PCI is yet another great resource, ideally suited for beginners to start their learning of complex machine learning algorithm development. It’s also a highly recommended book, endorsed by some of the most famous and established data scientists from around the world, a lot of whom have themselves read the book multiple times.
Interestingly, this book predates the era when machine learning and data science became the cult, still the topics covered in the books like collaborative filtering techniques, Bayesian Filtering, Support Vector Machine, and others are extremely relevant even today.
Written by Drew Conway and John Myles White, this book covers in detail the data analysis in R. Written with great clarity, this book is ideally suited for beginners with limited knowledge and wanted to excel in R programming in data wrangling. The books also detail interesting case studies to help readers with clarity and a better understanding of the application of machine learning algorithms.
Machine Learning by Tom M Mitchell
Once, you are done with the above-mentioned books, you can now dive into greater depths of machine learning. And this Machine learning book is ideally suited to start your advanced learning journey in machine learning. The books detail quite nicely the ML theorems, while also offering pseudocode summaries and case studies as an example for easy understanding of the readers. This is a highly recommended book by experts, who endorse it for the richness of the content, and interactive learning experience.
Top 10 Machine Learning Certification
Now, let us see in detail some of the best machine learning courses available online that can help you boost your career:
1) Professional Certificate Program in Machine Learning and Artificial Intelligence by MIT
It’s a highly recommended course for undergraduates, as well as, for professionals looking to boost their careers. The course is equally beneficial for individuals and businesses alike, to get hands-on experience with the power of AI and Machine Learning. With various actionable knowledge and best practices to implement, it prepares the participants to develop and implement their first machine learning algorithm. Delivered by the MIT experts, the course offers latest content and introduce participants with the state-of-the-art technologies and research required to build AI systems. The knowledge gained by the course could be put into practice by businesses and individuals to advance in cognitive technology.
$2500 – $5500
Undergraduate degree in computer science, physics, data mining, mathematics or electrical engineering with some basic understanding of programming languages.
Highly qualified MIT faculty and industry practitioners.
Develop essential skills and knowledge required to develop practical AI systems.
Interactive mode of learning, discussions with instructors about challenges posed by AI in the real-world environment.
Latest techniques and state-of-the-art knowledge in AI and machine learning.
Networking opportunity with experienced professionals from across the world.
2) Machine Learning with TensorFlow on Google Cloud Platform Specialization by Coursera
This specialized high intensity machine learning class comes with five courses designed stepwise to take participants from beginner level to expert. The initial courses gives the introduction to the machine learning technology, comprising of beginner-level lessons that introduce participants to the machine learning technology, what makes it so popular and what it is capable of achieving. Whereas the advanced courses gives you the skills and competence to build machine learning algorithms, focusing on Tensorflow which is an open-source machine learning framework.
The course is expertly designed in an interactive manner to train participants in development of machine learning algorithms, solve numerical problems and understand the work process that goes behind the development of ML models. The training course also include various assignments, offering excellent opportunity to participants to get a hands-on experience to build skills on ML model development leveraging the features available on Google Cloud Platform.
Every 2 Months (Coursera)
Financial Aid Available
Computer Science or Engineering Discipline
A comprehensive online course that takes you from beginners’ level to the development of your first ML model.
Develop first machine learning models and learn how to scale your models in Tensorflow.
Hands-on assignments and labs to enhance your skills using Google cloud platform.
A great opportunity to share your learning and projects with Google and Publicis to be considered for direct hiring opportunities.
Specialization certification that can be shared with potential employers and professional network for better hiring opportunities.
3) Machine Learning Stanford Uni Online
This is one of the best machine learning courses that gives the overview of the statistical pattern recognition and machine learning. The program details the differences between supervised and unsupervised learning algorithms, as well as, reinforcement learning and control. The course also gives the introduction to the latest machine learning design, development and applications.
August – September
Computer Science or Engineering Background
Introduction to the fundamentals of machine learning.
Generative learning algorithms.
Learn algorithms evaluation and debugging.
Value and policy iteration.
4) Professional Certificate in Foundations Of Data Science by Edx
This is a unique machine learning program that brings in new angle to explore issues and problems in ML. the program offers guidance to build skills in combining data with python programming skills, which can then be used in any field of study or job. For data science professionals, the program offers great resources to learn analysis of real data sets, including geographic, economic and social data. The course also include learning of inference, which is essential is quantification of uncertainty and accuracy measurement of estimates. All of the knowledge is smartly packaged together to teach prediction and forecasting using machine learning.
2-4 Months on Edx
4 Months (Self-Paced)
This course is specifically designed for beginners who do not have any computer or statistics background and no programming experience
Assess estimates by critical thinking from incomplete information.
Hands-on learning for analysis and visualization in Python 3.
Computational thinking and data analysis skills.
Prediction and forecasting based on machine learning.
Data interpretation using real-world examples.
5) Certification of Professional Achievement in Data Sciences by Columbia Uni
The course is a complete package that covers various courses including algorithms for data science, exploratory data analysis, machine learning for data science, probability and statistics. This course is ideally suited for participants with some basic skills in programming, calculus, statistics and linear algebra. The course enable students to enhance their skills in machine learning and improve chances to move up the professional career.
Online and Campus
Undergraduate degree with prior quantitative coursework for calculus, linear algebra, statistics and programming skills
Detailed overview of the computational thinking using Python.
Develop skills to use inferential thinking to come up with predictions about unknowns.
Learn machine learning for pattern identification with focus on regression and classification to make better predictions.
6) eCornell Machine Learning Certificate
As one of the best machine learning programs available online, the Cornell’s certification program equip students with the knowledge and skills to develop and execute machine learning algorithms using Python language. The program help students to use the math and intuitions to solve complex machine learning problems and develop mental models as a mean to understand the professional data scientists’ approach to solve these problems programmatically. Some of the machine learning algorithms covered in the programs includes; regression trees, k-nearest neighbors, naïve Bayes and others.
The course also enable students to apply algorithms on real-data, as well as, practice debugging to enhance the models through SVM and other methods. The course also give introduction to the working of neural networks, covering essential topics to equip students with the skills to develop and adapt neural networks from different data sets. The program use open-source Python programming language and Numpy library for exercises and assignments.
$3,600 or $565/Month
Online and Campus
Learn the essentials of machine learning to develop models and perform debugging.
Create face-recognition system.
Execute naïve Bayes algorithm.
Estimate probabilities distribution from various data sets.
Develop spam filter for emails using linear classifier.
Learn bias-variance trade-off to enhance the estimation and accuracy of algorithms.
Train a neural network.
7) Certificate in Machine Learning
This is a three-course certification that covers all aspects of machine learning. The program explores various machine learning concepts including statistical methods and probability which forms the foundation of machine learning algorithms. The course takes a practical learning method to implement machine learning concepts using open-source tools, while also assisting in developing judgement and intuitions to prepare students for real-world challenges.
Concepts of probability, statistical analyses, mathematical modeling, and optimization techniques.
Supervised and unsupervised learning models for tasks such as forecasting, predicting and outlier detection.
Advanced machine learning applications, including recommendation systems and natural language processing.
Deep learning concepts and applications.
How to identify, source and prepare raw data for analysis and modeling.
8) Harvard University Machine Learning
This machine learning course discuss in detail about principal component analysis and other widely used machine learning algorithms used in various industries. the course also explores the techniques to train datasets and develop predictive relationships, as well as, teaches overtraining techniques like cross validation.
Learn fundamentals of machine learning.
Learn to perform cross validation.
Learn different industry use machine learning algorithms.
9) Machine Learning with Python by IBM
The program covers the basics of machine learning technology using open-source Python programming language. The program content can be divided into two broad components, first where you learn about the purpose of machine learning and second where you learn the application of machine learning to the real world.
Learn the basics of machine learning.
Develop skills in specific machine learning algorithms like SciPy, regression, classification etc.
Certificate of proficiency in machine learning for better hiring opportunities.
10) Machine Learning at Udacity
This course covers two distinctive model, supervised learning and unsupervised learning in machine learning. For supervised learning, you get to develop model for email spam filtering and voice recognition, whereas, for unsupervised learning, you learn how Amazon knows what you want to buy or Netflix knows which movies you will like.
Year Round (Udacity)
Supervised Learning for beginners.
Unsupervised Learning for noobs.
Best Cheap Machine Learning Courses/Programs Alternative
- Data Science A-Z™: Real-Life Data Science Exercises Included (Kirill Eremenko/Udemy)
- Intro to Data Analysis (Udacity)
- Data Science Fundamentals (Big Data University)
How to follow Andrew ng machine learning course programming on python?
Here’s what you can do:
The course will include the programming assignments for Octave or Matlab, however, you would have to execute the equations in the assignment for the algorithms, which you can easily complete in Python using Numpy. Which means that you can essentially implement the assignments in the Andrew Ng. machine learning course in Python using Numpy. However, this would be more difficult, as here you would have to come up from the scratch for everything that’s needed to be done.
You should also start exploring the Scikit-learn, which completing the course. The Scikit-learn is a ML library in Python and comprise of algorithms, which you can import and use on different datasets you get in the course.
Which computer science course is best for machine learning?
Most employers looking for a ML expert would like to have applicants with a Masters’ degree in computer science, mathematics or related disciplines with proven experience in development and implementation of machine learning algorithms.
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