With the rapid advancement of technology, Machine Learning and Artificial Intelligence are among the highest-paid skills you can learn. To do so in 2023, you must learn the best machine learning courses online. But we can understand it can be a tedious and confusing task to choose among 1000s of courses that are on the internet.
Machine learning’s primary goal is around the idea that computers learn on their own. Artificial intelligence has a subclass called machine learning. Many organizations are using machine learning in their everyday operations.
Should I learn Machine Learning in 2023?
The answer is absolutely YES! The following advantages will ease your approach toward machine learning:
- A machine learning algorithm creates the world of tomorrow.
The way humans think has dramatically changed due to machine learning, which is now used successfully in many fields. Sooner or later, robots will do various tasks alongside humans in every nation.
- The need for a machine learning engineer is immediate.
As long as knowledge of machine learning is scarce and has a high barrier to entry, it is vital to have a machine learning engineer. We know that the typical software engineer will completely replace the machine learning engineer position. Thus, it is the best time to upskill yourself in this course.
- Aids in the analysis of consumer behaviour
Machine learning trends assess customers and monitor their day-to-day purchasing activity by examining various patterns. It efficiently uses association rule mining and corrects trends to the demands of potential customers.
- Improved and sophisticated security
A growing number of businesses can detect various fraudulent actions more quickly, thanks to machine learning. It uses a variety of algorithms to look for malware that targets endpoints. PayPal uses machine learning features to check for fraudulent transactions quickly.
Best Machine Learning Courses Online
1. Machine Learning Crash Course — Google AI
This course explains the fundamentals of machine learning through a package of courses that include interactive visualizations of algorithms in operation, real-world case studies, literature developed specifically for ML beginners, video lectures by Google researchers, and real-world examples. With coding exercises that guide you through creating models in TensorFlow, an open-source machine intelligence library, you’ll immediately put new ideas into practice as you learn them.
Course Details:
- Duration: 15 hours
- Level: Intermediate
- Fees: Free
- Modules: 3
Click here to start the course.
2. Machine Learning with Python IBM — Coursera
A moderate overview of machine learning and what it is will be given at the start of this course. Topics covered will include supervised vs. unsupervised learning, simple regression, linear vs. non-linear regression, and more.
In this online machine learning course, you will delve into categorization strategies using various classification methods, such as decision trees, K-Nearest Neighbors (KNN), and logistic regression.
You will showcase your abilities in the final project by creating, assessing, and contrasting various Machine Learning models using various techniques.
Course Details:
- Duration: 3-6 hours per week
- Level: Intermediate
- Fees: From ₹7980/-
- Modules: 3
- Certificate: IBM AI Engineering Professional Certificate
Click here to start the course.
3. Supervised Machine Learning: Regression and Classification [Andrew Ng Machine Learning Course]
With the help of this Coursera course, you can study the fundamentals of machine learning, including data mining, statistical pattern recognition, and logistic regression. Students take the course individually from pre-recorded lectures and readings because it is a MOOC.
His students praise Professor Andrew Ng for clearly explaining the mathematical ideas behind several branches of machine learning. It takes about eleven weeks to finish the 61 hours of material in the course. Each topic, such as linear regression with a single variable, has its week, which includes videos, quizzes, and readings.
Course Details:
- Duration: Approx. 33 hours to complete
- Level: Beginner
- Fees: ₹7980/-
- Certificate: Machine Learning Specialization Certificate
Click Here to start the course.
4.CS229: Machine Learning: Stanford Machine Learning Course
This is the best machine learning course on Coursera that thoroughly introduces statistical pattern recognition and machine learning. The topics covered include unsupervised learning, supervised learning, learning theory, reinforcement learning, parametric/non-parametric learning, and adaptive control.
The course will also cover the current application of machine learning to robotic control, bioinformatics, data mining, speech recognition, autonomous navigation, and text and web data processing.
Course Details:
- Duration: Approximately 3 months to complete
- Level: Beginner
- Fees: ₹7980/-
- Certificate: Machine Learning Specialization Certificate
Click Here to start the course.
5. Professional Certificate Program in Machine Learning & Artificial Intelligence – Mit Machine Learning Course
Utilize MIT’s newest machine learning and artificial intelligence techniques to navigate the evolving digital landscape and spot new chances for adding value. The Professional Certificate program is for working professionals dealing with predictive modeling and data analysis. The Professional Certificate can be obtained by passing at least one course in Machine Learning for Big Data and Text Processing.
Course Details:
- Duration: Courses must be taken within 36 months
- Who can opt: Professionals with a minimum of a bachelor’s degree in a technical field like statistics, computer science, physics, or electrical engineering and at least 3 years of professional experience
- Fees: $325 (non-refundable)
Click Here to start the course.
6. AWS Machine Learning Course on Coursera
Machine learning(ML) ideas that are applied to create AI applications, regardless of your degree of expertise. You can keep up with this progress, broaden your skills, and even advance your career by learning the ML fundamentals now. This machine learning course will guide you on how to get initiated with AWS Machine Learning.
The essential issues are AWS machine learning, natural language processing (NLP), and computer vision. Each topic is broken down into modules that go in-depth on various ML principles, AWS services, and expert perspectives on applying the concepts.
Course Details:
- Duration: Approximately 9 hours to complete
- Level: Intermediate
- Fees: ₹2361/-
- Certificate: Machine Learning Specialization Certificate
Click Here to start the course.
7. Deep Learning Prerequisites: Linear Regression in Python
Udemy has the best course in this niche. To get a deeper understanding of the “line of best fit,” linear regression—one of the fundamental tenets of deep learning—uses probability theory. You’ll learn the fundamentals of creating a Python linear regression module in this course before moving on to real-world machine-learning problems that will lay the groundwork for your study of deep learning.
Course Details:
- Duration: 6.5 hours of video
- Pre-requisites: How to use calculus to take a derivative and Python programming basics
- Level: Intermediate
- Fees: ₹3499/-
Click Here to start the course.
7. Machine Learning, Data Science and Deep Learning with Python
This is one of the best machine learning courses on udemy, which is Python-focused. You can use the practical Python code examples in this course as a reference and for practice. You will learn about Regression analysis, Sentiment analysis, Reinforcement Learning, Hyperparameter Tuning, Feature Engineering, and Deep Learning / Neural Networks with TensorFlow and Keras in this course, among other topics.
The benefits of these courses include a Certificate of Completion, lifetime access to the course materials, 6 articles, and 1 downloadable resource.
Course Details:
- Duration: 14.5 hours
- Level: Beginner (but need basic coding experience)
- Fees: ₹999/-
Click Here to start the course.
8. Introduction to Machine Learning on Udacity
You’ll understand core JavaScript, HTML, Python, and CSS. Thus, acquiring a thorough learning of coding principles through practical exercises and projects and developing your confidence to think and solve problems like a coder.
After completing this course, you’ll understand the basics of web development basics, Python I and Python II programming introductions, and JavaScript tutorial. This course is also a component of their Nanodegree in Data Analyst.
Course Details:
- Duration: Approx. 10 Weeks
- Pre-requisite: Experience in coding and data science
- Fees: Free
Click Here to start the course.
9. Intro to Machine Learning on Kaggle
You’ve arrived at the right place if you have some introduction to the machine learning experience and want to learn how to fast raise the caliber of your models. By studying the following skills in this course, you will advance your machine-learning expertise:
- Learn the data types that are frequently present in datasets from the real world (missing values, categorical variables)
- Create pipelines to enhance your machine learning code’s quality
- Apply cutting-edge methods for model validation (cross-validation)
- Construct cutting-edge models that are frequently utilized to win Kaggle contests (XGBoost)
- Avert typical and critical data science errors (leakage).
Course Details:
- Duration: 3 hours
- Level: Basic
- Fees: Free
Click Here to start the course.
10. Machine Learning with Python: Foundations on Linkedin Learning
The flexibility of Linkedin courses offers a manageable learning experience, as many online courses do. LinkedIn Learning’s monthly subscription is also a good investment if you intend to keep improving your skill set. In this course, Frederick Nwanganga straightforwardly presents machine learning.
He offers step-by-step instructions on how to begin using machine learning using Python, the most popular language currently. Frederick begins by explaining precisely what it implies for machines to learn and the many methods they learn before discussing how to gather, comprehend, and organize data for machine learning.
Course Details:
- Duration: 3 hours
- Level: Intermediate
- Fees: ₹1061/-
Click Here to start the course.
Best Machine Learning Course as per Reddit Users
11. edX’s Introduction to Artificial Intelligence (AI) course
Most Reddit users recommend edX’s Introduction to Artificial Intelligence (AI) course as the best. This course looks into the theories that underpin modern artificial intelligence, including the algorithms and principles that support technologies like handwriting recognition, machine translation, and gaming engines.
Students leave the course with knowledge of the fundamentals of artificial intelligence, expertise with libraries for machine learning, and the ability to create intelligent systems. This machine learning course is a self-paced course that is very comfortable for students and working professionals.
Course Details:
- Duration: Self Paced
- Level: Basic (Preferred CS50 or prior programming experience in Python)
- Fees: Free
Click Here to start the course.
Conclusion
After carefully knowing the top 11 best machine learning courses online and conducting a comparative analysis of the top machine learning programs available online, you will naturally gravitate towards the course that best suits your present and future needs.
Aspiring ML professionals now have more than easy access to education thanks to the widespread availability of MOOCs and for-profit certifications. We hope that this post has aided you in your search for the ideal machine learning course and helped you select the finest one for you. Thank you for reading, and good luck selecting the right course!
