11 Best Machine Learning Courses / Certification (2019)
Computers are quickly becoming smarter as Machine Learning, a subset of Artificial Intelligence (AI) makes tremendous developments in mirroring human thinking. If you didn’t know, Machine Learning is a science that aims to get computer systems to act without needing to be programmed.
A few years back, machine learning was offered in the form of self-driving cars, effective web search, practical speech recognition and the recognition of the human gene. Today, however, Machine Learning is so ubiquitous, so much that you undoubtedly use dozens of times in a day without even knowing it.
Why you should learn Machine Learning
According to a report by Gartner, the demand for artificial intelligence will surge by about 38% by 2020 (https://www.gartner.com/newsroom/id/3837763). A different statistic by Tractica states that Machine Learning is expected to grow its market value to $59.8 billion by 2025.
With these facts in mind, it is safe to say that now is the best time to invest in a Machine Learning course that will impart you with the knowledge needed to make your future brighter.
The advantages of taking an online Machine Learning course
These courses are perfect for those looking to achieve specific career goals within a short period of time. Most courses are geared towards specific career goals and will teach you how to apply Machine Learning in real life.
Unlike most university degrees, a Machine Learning course generally takes between one to six months to complete, depending on what you want to specialize in and your goals.
Saves on Cost
Machine Learning certifications generally don't cost as much as university degrees. This is majorly because these courses take a shorter duration and most are entirely online, doing away with operational overhead costs. This, in turn, makes them affordable, allowing people from all backgrounds to access them.
One of the biggest advantages of these courses is that they are available online. This means that you can study from anywhere in the world as long as you have a good internet connection.
Creating computer systems that automatically improve with experience requires many applications including data mining, robotic control, bioinformatics, and autonomous navigation. Fortunately, there is a wealth of readily available educational material online.
Even so, it is crucial that you choose the right fit for your interest. If you are considering taking a Machine Learning course, here are some of the top Machine Learning courses today.
Coursera: Machine Learning by Stanford
Price: Free + $99 for an official certificate
Duration: 11 weeks
Who is it for: This course is highly recommended for individuals looking to work in the AI or Data Science field or just wants to get a better understanding of these fast-developing and highly sought after skills.
Led by famed Professor Andrew Ng, the Stanford Machine Learning course is the highest rated onlineMachine Learning course today. It provides a comprehensive introduction to statistical pattern recognition and Machine Learning. The course is very practical and is designed for a non-math background. Therefore, you do not need ample knowledge in statistics, calculus, probability to enroll in this course.
That said, basic skills, including linear algebra and programming, are crucial for smooth completion of the course. It begins with a linear algebra refresher and explains, in simple terms, Machine Learning concepts such as cost function, gradient descent, and regularization among others.
Overall, this course is one of the best to start learning Machine Learning. It covers enough theory to clear your basic concepts and hands-on practice as well to ensure you can apply it in the real world. You will get a chance to explore recent applications of Machine Learning as well as design and develop algorithms for machines. Some of the topics covered in this course include;
• Policy and value iteration
• Generative learning algorithms
• VC dimension and Variance tradeoff
• The basic concepts of Machine Learning
• Debugging and evaluating learning algorithms
• Q-learning and value function approximation
You will also encounter numerous applications and case studies among other resources. During the course of your tuition, you will be equipped with real Machine Learning techniques as well as gain practice applying them in real-life cases and controlling them so that they work for you.
Other than the theoretical foundations of Machine Learning, you will also gain the practical expertise needed to powerfully apply these skills to problems.
• The course is crafted by some of the world’s top experts in Artificial Intelligence
• Specialization includes a capstone project and certification
• Its learning resources especially the video is of high quality
• Flexible class hours
• In-depth, comprehensive content
• Great career preparation
edX: Machine Learning Data Science by Harvard University
Price: Free + $99 for a verified certificate
Duration: 5 weeks
Who is it for: This is an introductory course to Machine Learning and is highly recommended for beginners looking to learn more about this growing field.
Led by Rafael Irizarry, the Professor of Biostatistics at Harvard University, this course provides an in-depth introduction to Machine Learning and algorithms. You will get a basic understanding of Machine Learning and come up with practical solutions using predictive analysis. It uses motivating case studies, asks specific questions and shows you how to answer them by analyzing huge amounts of data.
During the course of this program, you will learn;
• Statistical concepts
• Popular machine learning algorithms
• Data analysis techniques
• R programming language
These topics will be learned simultaneously by building a movie recommendation system. Some of the case studies covered include US Crime Rates, Trends in Global Health and Economics, election Forecasting, Movie Recommendation Systems, Building a baseball Team among other things.
You will learn about training data and how to use a set of data to discover potentially predictive relationships. You will also learn how to train algorithms using training data to predict outcomes of future datasets.
• You will get to learn in some of the best classes run by highly experienced professors
• They provide cool tools, game-like labs, videos and quizzes
• The course is flexible, meaning you can take it when you want to and study at your own pace
Udemy: Machine LearningA-Z™
Duration: 41 hours
Who is it for: This course is recommended for learners of all levels including beginners with basic knowledge of Python for Data Science or R programming and some high school level knowledge in mathematics.
Developed by Kirill Eremenko a Data Scientist & Forex Systems Experts, and Hadelin de Ponteves a Data Scientist, this is one of the top Machine Learning courses today.
Other than being extensive in terms of content, the course is organized in a way that learners across all levels will be able to grasp concepts easily. Learners are given the option to choose the language of their own and skip the other, or try out both. This ensures that the instructors go hand in hand with learners about both ML concepts and programming language.
This course covers topics like;
• Data processing
• Natural Language Processing
• Association Rule Learning
• Dimensionality reduction
• Deep learning
Udemy’s Machine Learning A-Z™ course is packed with practical exercises that are based on real-life examples. This gives you a chance to get some hands-on practice creating your own models. After the successful completion of this course, you will learn Machine Learning on both Python and R, build a great perception of most Machine Learning models, make accurate predictions, handle specific tools like reinforcement learning, Deep Learning, and NLP.
You will also be taught how to choose the right model for different problems. All you need to enroll for this course is basic high school mathematics.
• You get a chance to meet the Instructor via a podcast
• It offers interactive exercises for learners
• It has a comprehensive Q&A session, which answers most of the commonly encountered issues.
Udacity: Machine Learning Engineer Nanodegree
Duration: 6 months
Who is it for: This course is recommended for university-level computer science students looking to work in the tech industry or anyone curious about Machine Learning.
This is a great alternative to Coursera’s academia. This course teaches you a range of industry leading techniques to full-fledged deep learning, which help you to complete its well-crafted projects. Udacity’s Machine Learning Engineer Nanodegree course provides you with the necessary tips and resources needed to develop your technical skills through their self-paced, hands-on learning.
It will teach you the end-to-end process of investigation data through a Machine Learning lens and also how to apply what you have learned to a real-world data set. It provides interesting short videos that are fun to watch, with every algorithm being explained with examples that are in simple terms.
Some of the topics you will learn include;
• Machine Learning foundation
• Deep learning
• Supervised learning
• Unsupervised learning
• Machine Learning capstone
• Reinforcement learning
• 1 on 1 technical mentor
• Real-life projects from industry experts
• Offers a flexible learning program
Simplilearn: Machine Learning Certification
Price: $699 for self-paced learning and $799 for online classroom Flexi-Pass
Duration: 180 days
Who is this course for: Data scientist and graduates aspiring to specialize and build a career in Machine Learning and data science, and business analysts and experienced professionals who want to understand data science and get more insights.
This course provides students with practical learning on ML concepts and techniques such as supervised and unsupervised learning, heuristic and mathematical aspects, and hands-on modeling, which is designed to develop algorithms and prepare learners for the role of a Machine Learning Engineer.
Some of the topics covered include:
• Introduction goes AI and Machine Learning
• Techniques of Machine Learning
• Data processing
• Supervised and Unsupervised learning
• Deep learning
This course aims to make you an expert Machine Learning professional through experience specific tasks. You will master various Machine Learning theories and techniques like supervised and unsupervised learning, heuristic and mathematical aspects, and hands-on modeling to create algorithms and prepare you to become a Machine Learning engineer.
Their live online classes are conducted by a Machine Learning expert. Students also enjoy lifetime access to self-paced learning units. You can also exercise what you learn through the four real-life projects you undertake. Upon the successful completion of the course, Simplilearn provides learners with an industry-recognized course completion certificate with lifelong validity.
• Dedicated mentoring sittings from industry experts
• 24/7 support with committed project mentoring sessions
• Lifetime access to self-paced learning
Springboard: Machine Learning Bootcamp
Price: $4,500 one off price or $900 monthly fee
Duration: 6 months
Who is it for: This course is designed for people with a background in software engineering that are looking to become Machine Learning experts.
Springboard’s Machine Learning Bootcamp is an intensive career-focused, self-guided mentor-led Machine Learning course that comes complete with a job guarantee.
It is built to equip you to transition into the role of an expert Machine Learning professional. Other than the advanced concepts of Machine Learning that you will be equipped with, you will also get to develop production engineering skills.
During the course of this program, you will learn:
• An introduction to AI and Machine Learning engineering
• Data wrangling and statistics for AI
• Deep learning fundamentals like neural network principles
• Building and deploying large scale AI systems
• Natural language processing among others
With interactive class sessions, videos and other learning tools. This course has proven to be one of the best among other related courses. By the end of the course, you will have taken part in the designing of a Machine Learning system, built a prototype and deployed an app that can be accessed through API or web service.
According to the Springboard, if you do not get a job within months of completing the course and graduating, you will receive a full refund of your tuition money. Throughout the entire learning process, students receive support from their industry mentor, Springboard’s resident advisors, and the larger student and alumni community.
• 24/7 access to the student community
• One on one unlimited mentor support and weekly calls
• Job guarantee
upGrad: Diploma in Machine Learning
Duration: 11 months
Who is it for: This course is for software developers, big data engineers and data scientists looking to advance their careers.
upGrad Machine Learning course by Bengaluru (IITB) provides you with rigorous and industry relevant programs that are specifically designed and delivered in collaboration with renowned IIIT-Bangalore faculty leader professor Sadagopan.
This course focuses on statistics like using statistics to describe data and infer insights, using supervised and unsupervised learning, building Machine Learning models, natural language processing, graphics models, deep learning, reinforcement learning and neural networks among other topics.
You will also get a chance to work on cutting edge projects like building chatbot engines, using medical imaging to predict disease, predicting customer churn in the telecom industry among others.
Some of the topics covered in this course include;
• Machine Learning
• Graphical Models
• Statistics essentials
• Pre-program preparation
• Graphics models
• Deep learning and neural networks
You will get to learn innovative applications through projects created in collaboration with industry Image classifiers, chatbots and more. You will also master advanced learning and AI concepts.
Udemy: Machine Learning Bootcamp
Who is it for: Recommended for both beginners with some programming beginners and experienced developers and programmers looking to advance their career.
This is one of the best courses for mastering data science and Machine Learning.
It will show you how to utilize the power of Python to evaluate data, create striking visualizations, and use dominant Machine Learning algorithms, Here, you will learn how to use the most popular Python Machine Learning libraries like Seaborn, Matplotlib, NumPy, Plotly, Meeshkan, Keras, TensorFlow, and Scikit- Pluralsight. You'll learn:
• More than 100 High Definition video lecture and comprehensive code notebooks for each lecture. Some of the topics to expect include
• Web Scraping Python
• Programming with Python
• Connecting Python to SQL
• NumPy with Python
• Linear Regression
• Support vehicle machines among others.
Higher School of Economics: Advanced Machine Learning
Price: $49 per month
Duration: 8 to 10 months
Who is it for: This course is recommended for analysts, developers and researched with basic knowledge of linear algebra, probability, and python.
This course offers an advanced level of specialization to get students closer to mastering more advanced practices like reinforcement learning and deep learning. The coursework covers various types of Machine Learning goals and objectives such as natural language processing and computer vision and how architectures such as convolutional neural network contribute to advances in image processing.
You will also get a chance to mingle with CERN and Kaggle Machine Learning experts who will provide hands-on examples of implementing Machine Learning in the real world. This course is built as a program that allows students to apply Machine Learning expertise in the enterprise.
• Flexible deadlines and 100% online
• Advanced level
• Hands-on project
Google Cloud: Machine Learning with Tensorflow
Price: $49 per month
Duration: 9 weeks
Who is it for: This course is recommended for data engineers and programmers interested in learning how to apply Machine Learning in practice, and anyone interested in learning how to build and operationalize TensorFlow models.
TensorFlow is quickly becoming a popular technology for Machine Learning, because of how it makes it easy to build powerful and sophisticated neural networks. This course will teach you how to write different Machine Learning models that rank in Tensorflow and scale out other training in those models to offer high-performance forecasts.
You will learn how to convert raw data into features while allowing ML to learn important features from the data to provide insight into the issue at hand.
You will also learn how to integrate the right mix of limits that yield accurate, comprehensive models and information on the theory to unravel different types of Machine Learning problems.
This course aims to develop a data strategy around Machine Learning, recognize that biases that Machine Learning can amplify and leverage Google Cloud platform tools and environment to do Machine Learning. You will also get to experiment with all-encompassing Machine Learning, from creating focused strategies and continuing into optimization, model training, and productionalization with practical test centers through the Google Cloud Platform.
• Flexible schedule
• The course is free
• Takes a relatively short time to complete
Imperial College of London: Mathematics for Machine Learning
Price: $49 per month
Duration: 2 months
Who is it for: This course is ideal for students starting a career in data science and professionals looking to advance their careers.
Get a Master’s degree in Machine Learning from one of the top universities in the world.
Imperial College London’s Machine Learning course is designed to propel your engineering or data science career forward. It aims to develop an in-depth understanding of Machine Learning models alongside practical skills and guided projects to help you apply it in the real world.
This course focuses on the mathematics behind Machine Learning, how to make it and how to create a bridge to practical training technologies. This helps you to become proficient at creating the types of work that Machine Learning involves.
Dimensionality reduction and multivariate calculus among other key components of this course will help you understand the inner workings of neural technologies and similar technologies to become proficient in these essential building blocks.
To enroll in this program, you will need some knowledge of Python as a programming language, and a basic understanding of the math used in Machine Learning such as linear algebra. This is an open Machine Learning course that is designed to perfectly balance practice and theory. Hence, each topic is followed by an assignment. You can also take part in several Kaggl in-class competitions that are held during the course as well as do your own projects.
• The course is practical and designed to help you master skills to enhance or build your career
• The classes are innovative with hands-on projects and the world’s best instructors.
• Their classes are interactive with global networks of instructors, classmates, and alumni.
If you want to dive into Machine Learning, these courses are a great place to start. The best part about them is that they are all available online. With utter commitment, these courses will help you learn and excel in Machine Learning. They are suited for people of all levels, including beginners, intermediate and expert learners.