According to recent studies, the demand for machine learning skills is increasing exponentially. This is because machine learning is becoming increasingly important in various industries, including healthcare, finance, and manufacturing. Taking up free machine learning courses and upskilling will help you stay updated with the industry requirements. 

If you are interested in building a career in machine learning but don’t know where to start, this blog is for you! We have curated a list of free machine learning courses to help you kick-start your journey. 

Top 11 Free Machine Learning Courses

The demand for machine learning has increased rapidly over time. Upskilling with the help of free machine learning courses can help you power ahead in your career. We have curated a list of free online courses that will help you step into the world of machine learning and enhance your skills and knowledge. Let’s get started!

1. Basics of Machine Learning

Machine learning is being widely used in several industries today. From building recommendation systems to spam filtering, machine learning is used everywhere. With the increasing amount of data available, making sense of this data provides businesses with a competitive edge. Enrolling in this basics of machine learning free online course will help you understand the fundamentals required for you to enter the field of machine learning. 

Skills:

• Introduction to machine learning
• Linear regression

2. Python for Machine Learning

A high-level programming language with an easy-to-use syntax, Python is one of the most popular programming languages. Python is an important programming language when it comes to Machine Learning. In this free Python for Machine learning online course, we will start by learning about a library known as NumPy. We will also learn about a core library in Python known as Pandas. The course syllabus is as follows:

• Introduction to NumPy
• Joining NumPy Arrays
• NumPy Intersection & Difference
• NumPy Array Mathematics
• Saving and loading NumPy Array
• Introduction to Pandas
• Pandas Series Object
• Introduction to Pandas Dataframe
• Pandas Functions 

3. Statistics for Machine Learning

Statistics is a branch of mathematics that deals with collecting, analyzing, interpreting, presenting, and organization of data. Applying statistics to machine learning can help provide a strong foundation for data analysis. This free online statistics for machine learning course provides the basic knowledge about descriptive statistics and data visualization. 

Course syllabus:

• Introduction to descriptive statistics
• Data and histogram
• Central tendency and 3 M’s
• Standard deviation
• Coefficient of variation
• Data visualization
• Correlation Analysis
• Descriptive statistics using Python

4. Machine Learning Algorithms

Machine learning is being widely used in almost every industry today. A well-tuned machine learning model can be very powerful and efficient at solving problems. However, this can be possible only because data is fed into the algorithms. Having a clear understanding of machine learning algorithms will help you comprehensively implement concepts such as supervised learning, unsupervised learning, etc. In this free online machine learning algorithms course, you will learn the following: 

• Introduction to machine learning
• Types of machine learning
• How does a machine learning model learn?
• Linear regression algorithms
• Naive Bayes algorithms
• KNN algorithms
• Support vector machines
• Random forest algorithm 

5. Application of Machine Learning in Finance

As we know, machine learning is widely used in almost every industry today. By implementing machine learning in finance, we can drive operational efficiency in various aspects, such as risk management and trading to insurance underwriting. The financial sector has seen several benefits of the application of machine learning. In this free online application of machine learning in finance course, you will learn more about the different use cases of machine learning in finance. This course has been designed for beginners who wish to learn more about the subject. 

6. Unsupervised Machine Learning with K-means

The k-means algorithm is a popular technique used to analyze unlabeled datasets. Unsupervised machine learning is a widely used machine learning technique. In this unsupervised learning with k-means free online course, you will learn about machine learning and its types, what unsupervised learning means, and unsupervised learning models such as k-means clustering, numpy, pandas, scikit learn, and more. 

Course syllabus:

• What is machine learning?
• Types of machine learning
• What is unsupervised learning?
• Unsupervised learning models
• K-means clustering
• How can we decide the K-value?
• Demo on k-means

7. Supervised Machine Learning with Logistic Regression and Naïve Bayes

Supervised machine learning is the process of teaching a machine to recognize patterns using a set of training data. The machine is “supervised” because it is given feedback on its performance after each training data is presented. In this free online supervised machine learning with logistic regression and naive Bayes course, you will learn about logistic regression and naive Bayes algorithms. 

Course syllabus:

• What is machine learning?
• What is supervised learning?
• What is logistic regression?
• Demo on logistic regression
• What is Naive Bayes?
• Demo on Naive Bayes

8. Python Libraries for Machine Learning

Python libraries are collections of modules that allow you to perform specific tasks in your Python code. For example, the math library contains modules that allow you to perform mathematical operations. In this free Python libraries for machine learning course, you will be introduced to some of the widely used python libraries such as pandas, numpy, seaborn, matplotlib, etc. 

9. Machine Learning Interview Questions and Answers

If you’re preparing for an upcoming machine learning interview, this free machine learning interview questions and answers course is for you! The course will help you learn more about the type of questions you can expect in your upcoming interviews. It will help you revisit the concepts of machine learning and be prepared to land your dream job. 

10. Supervised Machine Learning with Tree-Based Models

Tree-based classifiers are used for finding insights from raw data and making important decisions. To understand the importance of tree-based classification models, we have created this free online supervised machine learning with tree-based models course. It will help you learn about supervised learning techniques such as random forests and decision trees and how to implement them in Python. 

Syllabus:

• Introduction to decision tree
• Demo for decision tree
• Introduction to random forest
• Demo for random forest

11. Introduction to Machine Learning in AWS

This free online machine learning in AWS course is designed for beginners. It is an introductory course and talks about cloud computing, its functions, the various cloud providers, what AWS means, and much more. You will gain a deep understanding of how machine learning and AWS go hand-in-hand. By the end of the course, you will gain the following skills: data science, machine learning, cloud computing, and AWS services. 

Closing Thoughts

Individuals with Machine Learning skills are in high demand. Upskilling with the help of free machine learning courses will help you land a high-paying job. You can also take up a postgraduate program in machine learning and gain a more comprehensive understanding of the concepts.