10 Best Online Courses For Machine Learning in 2024

Looking to dive into the exciting world of Machine Learning? You’re in the right place! Machine Learning is one of the hottest fields in computer science, with companies across industries embracing its potential. Whether you’re a working professional looking to upskill or someone eager to explore new horizons, online courses offer a flexible and affordable way to learn.

In this article, we’ll explore some of the best online courses from top universities and platforms. These courses will not only teach you the basics of Machine Learning but also empower you to apply these concepts in real-world projects. Get ready to embark on a learning journey that could transform your career trajectory—explore the best online courses for Machine Learning today!

What is Machine Learning?

Machine Learning is a branch of artificial intelligence (AI) that enables computers to learn from data and improve their performance on tasks without being explicitly programmed. It focuses on developing algorithms that can analyze and interpret patterns in data to make predictions or decisions. In essence, machine learning algorithms learn from experience, allowing them to adapt and improve over time without human intervention. This technology is widely used in various fields, including finance, healthcare, marketing, and more, to automate processes, optimize strategies, and gain insights from large datasets.

Best Online Courses For Machine Learning

These courses cater to beginners as well as those with some background in programming and statistics, offering a structured learning path that covers everything from the fundamentals to advanced topics. Whether you prefer self-paced learning or a more guided approach with assignments and quizzes, there’s a course out there to suit your learning style. So, take your pick from these top-rated and best online courses for Machine Learning and embark on your journey to mastering Machine Learning!

1. Complete Machine Learning & Data Science Program (GeeksforGeeks)

This is one of the most versatile and trusted by thousands of candidates that teach you the basics of Machine Learning and later it moves on to the advanced level. This course will drive you through various machine learning principles and by the end of this course, you’ll be able to learn how to deploy different models of machine learning to solve real-life problems. 

This machine learning course provides an introduction to Data Science and differentiates AI, ML, and DL for better clarity. As you move forward, this course will take you forward in Jupyter, Numpy, and Data Analysis with Python for better understanding. This 125+ hours course will also cover brief on:

• Linear Regression
• Multiple Linear Regression
• Polynomial Linear Regression
• Support vector machine
• Decision Tree
• Random forest
• Classification Algorithms
• Clustering Algorithms
• Feature Engineering

This 360-degree Learning experience course also offers live projects for the best experience in Data Analysis, Data Prep, Classification, Sentiment Analysis, Working with Medical Data, etc. Although it’s a lifetime accessible course, students can complete it within the span of 3-6 months duration and a certificate will be issued by the name of the enrolled person which can be added to the resume or LinkedIn profile.

Course Link: Complete Machine Learning & Data Science Program

2. Supervised Machine Learning: Regression and Classification by Stanford University (Coursera)

This is the most famous Machine Learning course on the internet! This course aims to teach both the theoretical aspects of Machine Learning algorithms as well as the practical implementations. This Machine Learning course covers:

• Supervised Learning
• Unsupervised Learning
• Linear Regression
• Vectorization
• Feature Scaling
• Polynomial Regression along with the 4 practical exercises. 

This course can be completed over a period of 3 weeks and it covers multiple aspects and applications of Machine Learning. You can also learn to apply these learning algorithms for computer vision, database mining, text-understanding, creating robots, etc. After completing this course, you will obtain a Shareable Certificate that you can display on your resume or LinkedIn profile.

3. Deep Learning Specialization by DeepLearning.AI (Coursera)

This is an advanced specialization for Deep Learning provided by Andrew Ng (co-founder, of Coursera). Once you complete the Machine Learning course, you will have in-depth knowledge of deep learning topics like:

• Convolutional networks
• Recurrent neural networks
• Long short-term memory (LSTM)
• Natural Language Processing, etc. 

This course will also provide personal stories and career advice from many top leaders in Deep Learning which will enrich your experience. This Deep Learning specialization has 5 courses including Neural Networks and Deep Learning, Improving Deep Neural Networks, Structuring Machine Learning Projects, Convolutional Neural Networks, and Sequence Models. You will also create deep learning models in many different fields like autonomous driving, healthcare, natural language processing, music generation, etc. After completing each of the courses in the specialization, you will obtain a Shareable Certificate that you can display on your resume or LinkedIn profile.

4. Machine Learning with Python by IBM (Coursera)

This course aims to teach you Machine Learning using Python. First, you will learn the basics of Machine Learning and its applications in the real world and then move on to the Machine Learning algorithms such as:

• Regression, Classification
• Clustering algorithms. 

The course is divided into six-weeks with each of them focusing 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, etc., Clustering algorithms including  Hierarchical Clustering, Partitioned-based Clustering, and Density-based Clustering, Recommender Systems.

And the last week contains a Final Project that would utilize whatever you have learned. After completing this course, you will obtain a Shareable Certificate that you can display on your resume or LinkedIn profile.

5. Machine Learning Specialization by the UW (Coursera)

This Machine Learning Specialization aims to teach ML using theoretical knowledge and practical case studies that will teach you about:

• Regression algorithms
• Classification algorithms
• Clustering algorithms
• Information Retrieval

So this Specialization will teach you to create intelligent applications, analyze large datasets, etc. using the power of Machine Learning. 

This Specialization is divided into four courses including Machine Learning Foundations, Regression taught using a case study on predicting housing prices, Classification taught using a case study on sentiment analysis and Clustering & Retrieval taught using a case study on similar document finding. This specialization will take approximately 7-months to complete and after completing each of the courses, you will obtain a Shareable Certificate that you can display on your resume or LinkedIn profile.

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

This course from Columbia aims to teach you the fundamentals of Machine Learning and its different algorithms. It will also allow you to obtain solutions for real-world problems using predictive analytics by understanding the principles of Machine Learning. This course will focus on Machine Learning algorithms such as:

• Linear Regression with One Variable
• Linear Regression with Multiple Variables
• Logistic Regression
• Support Vector Machines
• Unsupervised Learning, etc.

Lastly, how to make data predictions by data analysis and using topic modeling to find the hidden meaning in large amounts of data.

At the end of this course, you will obtain an instructor-signed certificate from edX and ColumbiaX to demonstrate your knowledge of Machine Learning for Data Science and analytics.

7. Machine Learning with Python by IBM (edX)

This course aims to teach you Machine Learning using Python. First, you will learn the basics of Machine Learning using Python and transform this theoretical knowledge into practical skills using online labs. 

This course is divided into five weeks with each of them focusing on an Introduction to Machine Learning, Regression algorithms including Linear, Non-linear, and Model evaluation methods, Classification algorithms including K-Nearest Neighbour, Logistic Regression, Decision Trees, Support Vector Machines, etc., 

• Unsupervised Learning including
• Hierarchical Clustering
• K-Means Clustering,
• Density-Based Clustering

Recommender Systems. At the end of this course, you will obtain an instructor-signed certificate from edX and IBM to demonstrate your knowledge of Machine Learning using Python.

8. Data Science: Machine Learning by HarvardX (edX)

This course aims to teach you the fundamentals of Machine Learning and the different learning algorithms, principal component analysis, and regularization by creating a movie recommender system. You will also learn about data analysis and training data to obtain useful insights. This course will focus on Machine Learning algorithms such as:

• Linear Regression with One Variable
• Linear Regression with Multiple Variables
• Logistic Regression
• Support Vector Machines
• Unsupervised Learning

At the end of this course, you will obtain an instructor-signed certificate from edX and HarvardX to demonstrate your knowledge of Machine Learning for Data Science and analytics.

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

As the name claims, this course aims to teach you the basics of Machine Learning and Data Science from A-Z! This course is perfect for students who want to learn Machine Learning and Data Science or for professionals who want to make a career in these fields. 

Machine Learning A-Z teaches machine learning in both Python and R with a focus on more specific topics like Deep Learning, Reinforcement Learning, Natural Language Processing, etc. This course has a content structure with topics like:

• Data Preprocessing,
• Regression,
• Classification
• Clustering
• Association Rule Learning
• Reinforcement Learning
• Natural Language Processing
• Deep Learning
• Dimensionality Reduction
• Model Selection & Boosting

After completing the course, you will get a certificate of completion that you can display on your CV, LinkedIn profile, etc.

10. Python for Data Science and Machine Learning Bootcamp (Udemy)

The Python for Data Science and Machine Learning Bootcamp will teach you how to use Python for Data Science and Machine Learning along with the various Python libraries. You will use Pandas for Data Analysis, SciKit-Learn for Machine Learning, Seaborn for data visualization plots, Spark for Big Data Analysis, Plotly for interactive dynamic visualizations, Matplotlib for Python Plotting NumPy for Numerical Data, and so on. You will also learn various machine learning algorithms like:

• Logistic Regression
• Linear Regression
• Random Forest
• Decision Trees, Support Vector Machines
• Neural Networks, etc. along with SQL for databases.

This course is one of the most detailed courses for Data Science and Machine Learning on Udemy with over 100 HD video lectures and detailed code notebooks for every lecture. 

And after completing the course, you will get a certificate of completion that will demonstrate your knowledge of Data Science and Machine Learning.

Conclusion

Nevertheless, Machine Learning has created heat in the tech industry and people are continuously finding their way into this field. Being one of the most important components in Data Science, it teaches you how to solve real-life problems and master the fields of Mathematics, Python, Statistics, etc. Based on user input and popularity, we fetched out a list of the 10 Best Machine Learning Courses that you can opt-in for and these best machine learning courses are the live example of how you can start or deviate your career into the field of Machine Learning today.