Machine Learning is among the most intriguing and fast-paced computer science subjects with strong foundations in statistics. One of the key factors that drive the popularity of machine learning is its wide range of applications in various industries.
Machine learning models are used in chatbots, spam filtering, ad serving, search engines, and fraud detection, to name a few. It also helps developers discover patterns and create mathematical models to accomplish tasks that would otherwise be hard for humans to do.
To learn machine learning and become a skilled machine learning engineer, the best way is to enroll in certification programs and courses. Also, in contrast to data science certifications, machine learning certifications focus solely on machine learning algorithms, how they operate mathematically, and how to use them for solving real-world challenges.
In this article, we will help you become familiar with the most popular machine learning certifications available online. But first, let’s take a quick look at the concept of machine learning.
What is Machine Learning?
Machine learning is a subfield of artificial intelligence. It focuses on providing machines the ability to learn and take actions that are more human-like. Also, this is done with the least amount of human participation possible, and the learning process is automated and refined based on the experiences gained during the process.
Machines are fed high-quality data, and different methods are utilized to develop machine-learning models based on that data.
Businesses can automate ordinary processes with the help of machine learning. It also aids in the automation and rapid development of data analysis models. Various industries rely on massive amounts of data to improve their operations and make smart decisions, and for them, machine learning is the best weapon.
How to Choose the Ideal Machine Learning Course?
This blog post compiles a list of the best machine learning courses currently available on popular e-learning platforms. However, one should consider the following points for making an ideal decision:
- The course should teach you open-source programming languages like Python and R along with the usage of open-source libraries.
- Avoid considering a course whose instructors and providers use commercial software.
- Certifications with programming exercises to provide hands-on experience are the best.
- The course should be self-paced, on-demand, or only offered once or twice a month.
- A good certification offers intriguing lectures delivered by experienced instructors and has above-average reviews and ratings.
Before you enroll in an advanced machine learning certification program, you must have a firm understanding of the following topics:
- Linear Algebra
Additionally, many machine learning courses require you to have at least some programming experience as well as a fundamental understanding of linear algebra concepts like vectors, matrices, and notation.
Best Machine Learning Certifications and Courses
Following is a list of the top 10 machine learning certifications. You will get a brief overview of each certification so that it becomes easier for you to choose one that meets your requirements.
This applied learning course can assist you to develop a solid understanding of machine learning concepts. It will help you to know how machine learning works in the real world. Also, you will be able to learn about data analytics, wrangling, statistics, and Python programming.
The certification program is provided in partnership with Purdue University to help you gain knowledge about machine learning algorithms from industry leaders and qualified educators. You will get access to world-class education, outcome-focused boot camps, and hands-on projects.
- It covers various topics, including feature engineering, time series modeling, recommendation systems, and decision trees.
- You will learn Python programming fundamentals, data operations, shell scripting, conditional statements, and the Django framework.
- 48 hours of live online lectures from industry experts.
- You will operate real-time datasets from the healthcare and financial services industries in integrated labs.
Created by Andrew Ng, who is a former head of Google Brain and Baidu AI Group, this is a machine learning certification by Stanford University. It is one of the most sought-after certification courses available in the market. It’s no small thing for an ML certification to receive a 4.9 out of 5 ratings, and the fact that it’s affiliated with Stanford University just increases the program’s reputation.
Supervised learning, unsupervised learning, best practices in machine learning, are some topics that it covers. Also, the program structure is based on multiple case studies and applications. At the end of this certification program. you will be able to apply algorithms for text understanding, medical informatics, data mining, and much more.
- This course is one of the best ways to learn machine learning concepts and techniques.
- You will get a wide exposure to machine learning, data mining, and statistical pattern identification.
- Learn how to use machine learning algorithms to create smart robots, test comprehension, and computer vision.
- Take advantage of a variety of video lectures, guides, notes, and practice exercises to strengthen your knowledge.
- Earn a professional credential that you may use to show potential employers your abilities as a machine learning engineer.
With over 2.5 quintillion bytes of data generated every day around the world, it’s reasonable to say that data is king. This specialization, which consists of five courses, will take you from an overview of the relevance of machine learning to lectures on how to develop ML models.
The program begins with an overview of what machine learning is and why it has become so popular, followed by classes focused on Tensorflow, an open-source machine learning platform.
The video lectures in this certification program will teach you how to develop, train, and deploy machine learning models, as well as how to handle numerical issues. You will also understand how to improve the accuracy of machine learning using the Google Cloud Platform.
- This course will teach you all you need to know about machine learning, from basic concepts to real-world problems that it can address.
- Learn how to use TensorFlow to develop distributed machine learning models that are easily scalable.
- Learn how to combine the correct set of parameters to create accurate, generalized models.
This Nanodegree program aims to help you improve your machine learning knowledge. You can improve your practical knowledge by training, assessing, and evaluating models using Azure machine learning. It is an ideal course for people having prior knowledge of machine learning algorithms.
This machine learning certification will guide you to build and deploy sophisticated machine learning solutions with popular open-source tools and frameworks. Also, it features a capstone project at the end of the course that allows you to apply the various machine learning concepts to solve real-world challenges.
- The course is an intermediate-level certification that teaches you how to use various machine learning concepts and open-source tools.
- With the Azure labs available through the Udacity classroom, you can gain practical experience by accomplishing various machine learning tasks.
- Learn how to set up machine learning pipelines in Azure and uncover automated machine learning use cases.
- Learn how to test the model endpoint and publish the machine learning model as a web service.
This ML certification by Harvard will help you understand various concepts, including R. Probability and Linear Regression.
You’ll also learn about inference and modeling, productivity tools, and wrangling, all of which will be followed by a Capstone Project to help you implement your knowledge. Rafael Irizarry, Professor of Biostatistics at Harvard University, is the instructor for this course.
- Learn basic R programming skills as well as statistical principles such as modeling and inference.
- Learn how to use tidyverse and perform data visualization with ggplot2 and data manipulation with dplyr.
- Develop a core set of skills in R programming, data visualization, Unix/Linux file organization, and repeatable document creation.
- Access inspiring case studies, pose precise questions and learn by answering them through data analysis.
- Utilize video lectures and case studies to gain a thorough understanding of core data science concepts.
- Once you’ve completed the course and cleared the required projects and tests, you’ll be awarded a professional certificate.
This is a wonderful machine learning certification if you’ve decided to become a data scientist or machine learning engineer. It has nine different sections that will help you learn the skills that you’ll need to work on industry projects.
Data visualization, analysis, libraries, and open-source tools are some of the topics covered in this course. By the end of the program, you will have completed a variety of assignments and projects that will allow you to demonstrate your abilities as a data scientist.
- This is an introductory course aimed at teaching the basics of machine learning and data science.
- Learn from industry experts who have been with IBM for many years.
- To help you prepare for the certification exam, you will be provided with a variety of video lectures, exercises, and quizzes.
- Get round-the-clock assistance from a team of professionals who will guide you at every point of the course.
This course helps in assisting individuals to develop a strong foundation in mathematics, as well as have an intuitive grasp of how to apply it to machine learning and data science. Before moving on to more complicated concepts, the course talks about Linear Algebra and Multivariable Calculus.
You will develop a strong mathematical foundation by the end of the classes, allowing you to create more complex ML programs.
- This program consists of three separate classes, each of which focuses on clearing various mathematical concepts to focus on machine learning.
- Understand linear algebra, how it correlates to data, and how to use vectors and matrices to solve problems.
- With the use of multivariate calculus, learn how to optimize fitting functions for good data fits.
- Learn from a group of highly qualified instructors who will also assist you with any course-related questions.
Coursera offers a variety of machine learning certifications, as well as specialized courses that focus on certain important aspects of machine learning. This specialized course is created by Washington University’s top researchers. It will teach you how to evaluate huge and complicated datasets and introduce you to the intriguing and in-demand discipline of machine learning.
If you want to become a machine learning expert, this specialist course can be of great help. It offers hands-on tasks that you must finish to complete the course successfully.
- Gain experience in important areas of machine learning such as prediction, classification, and data extraction.
- Learn how to design intelligent applications that can draw conclusions based on data and improve over time.
- The course comes with a 30-day free trial and enables you to study at your own speed.
- Practical exercises, video lectures, and quizzes help you to improve your knowledge and skills effectively.
So far, around 794,416 students have enrolled in this Machine Learning course, which has received a rating of 4.5 stars out of 5. Kirill Eremenko and Hadelin de Ponteves, together with their Super DataScience Team, have put together this amazing program to assist you in developing Machine Learning algorithms in Python and R.
To attend this class, you only need a high school level knowledge of mathematics or a rudimentary awareness of algorithms such as linear regression and logistical reasons. It is a 40.5 hour-long comprehensive course that will provide you with all of the information and knowledge you need to succeed as a machine learning engineer.
- Offers step-by-step instructions to teach you the fundamentals of machine learning.
- Real-life examples to help you learn better.
- Learn how to create powerful machine learning models and use them to solve complex problems
- Get a certificate of completion after accomplishing all the projects and assignments.
This course by HSE University for Machine Learning Specialization includes seven modules that cover a wide range of machine learning concepts. You will learn how to create highly effective systems or solutions based on machine learning. Also, you will receive your machine learning certificate after completing all the modules as well as the hands-on project.
To enroll in this specialized course, you must have a basic understanding of machine learning, probability theory, linear algebra and calculus, and Python programming. Thus, it is recommended that you first take a beginner’s machine learning course to brush up on your skills before moving on to this certification program.
- Learn how to utilize some of the most popular and effective machine learning tools.
- Adopt excellent data exploration, preprocessing, and feature engineering approaches.
- Combine deep models and traditional computer vision methods to solve computer vision challenges.
- Create goal-oriented conversational bots and teach them how to converse in a human-like manner.
- Recognize the limitations of traditional machine learning methods and create new algorithms to solve advanced problems.
After mastering machine learning, you can easily pursue a career in several fields, including data science, data analysis, business intelligence, and business analytics.
This will also improve your chances of landing a job as a data scientist. Many organizations today are extensively looking for individuals having machine learning knowledge. And this is high time for programmers to explore this domain in terms of skills, growth, and job security.
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