This article lists the best places to acquire AI and ML certification along with the USPs of the various schools listed. It is an enlightening read for freshers and professionals seeking to advance in their chosen fields and for those who want to venture into new fields.
With education going online and being made available from some of the world’s best institutions, those of us who are constant learners could exploit the current lockdown to study further. An exhaustive list of options is featured here.
The Best Artificial Intelligence Certifications [2020]
- Artificial Intelligence (Northwestern University | Kellogg School of Management)
This course has been created for individuals looking forward to learning about the strategies and techniques of artificial intelligence to solve business problems. After the fundamentals are covered, you will understand how AI is impacting different industries as well as the various tools used for developing efficient solutions. By the end of the programme, you will have numerous strategies under your belt that can be used to improve the performance of your organisation.
USPs
- Learn to manage customer expectations and develop AI models accordingly.
- Multiple case studies that allow you to get a better understanding of the challenges faced in the real world.
- Get answers to your queries from a dedicated support team.
- Complete the exercises and get feedback on your performance.
- Work with data based on real-life case studies.
- Pass the exam with at least 80 per cent to earn the certification.
- Machine Learning (ML) AI Certification by Stanford University (Coursera)
If learning ML is your objective, then there is no need to look further. Created by Andrew Ng, a professor at Stanford University, more than 2,612,800 students and professionals who enrolled in this programme from around the globe have rated it very highly. This course provides an introduction to the core concepts of this field such as supervised learning, unsupervised learning, support vector machines, kernel and neural networks. Students get to draw from numerous case studies and applications, and can go hands-on to apply the theoretical concepts to practice. By the end of the classes, you will have the confidence to apply your knowledge to real-life scenarios.
USPs
- Understand parametric and non-parametric algorithms, clustering and dimensionality reduction, among other important topics.
- Discover best practices and get advice from the instructor.
- Interact with your peers in a community of like-minded learners from all levels of experience.
- Real-world based case studies give you the opportunity to understand how problems are solved on a daily basis.
- IBM AI Engineering Professional Certificate (Coursera)
If you want to be a part of the fast-paced field of AI, then this professional certification programme can open the right path for you. This programme consists of six different courses that will provide you with a practical understanding of machine learning and deep learning concepts. In this course, you will learn the fundamental concepts of ML and DL, with both supervised and unsupervised learning. This course is designed by an experienced faculty from IBM to help individuals cover every essential topic related to artificial intelligence. Only after finishing all the six courses will you receive a professional certificate in AI engineering.
USPs
- Learn how to use the popular ML and DL libraries like SciPy, ScikitLearn, PyTorch, etc.
- Learn how TensorFlow is applied to industry problems involving text analytics, object recognition, natural language processing and other types of classifiers.
- Dive into the individual concepts of ML with Python, an approachable and professional programming language.
- Obtain the skills to scale data science and ML tasks on Big Data sets using Apache Spark.
- Be able to build, train and deploy different types of deep architectures, as well as convolutional networks, recurrent networks and auto-encoders.
- Artificial Intelligence: Business Strategies and Applications (Berkeley ExecEd)
This course is designed for senior leaders, managers and functional business heads who are interested in exploring AI opportunities across their business functions. This programme will introduce you to the basic applications of AI, its capabilities and potential while offering in-depth information about automation, machine learning and robotics. It consists of eight different modules focused on various concepts, such as ML, AI strategy, key applications, neural networks, etc. At the end of the programme, a capstone project will be given to you to showcase what you have learned through the course. Completing the capstone project will make you eligible to receive the certificate of completion.
USPs
- Designed with a hands-on approach that will help you build a bridge between engineering and the technical aspects of AI with business applications.
- Learn how to organise and manage successful AI application projects while avoiding the pitfalls associated with these new technologies.
- Grasp the technical aspects of AI so that you can communicate effectively with technical teams and colleagues.
- Build your leadership credibility by obtaining a certificate of completion from the UC Berkeley Executive Education programme.
- Gain continuous support and assistance from the world-class faculty who will help you understand the critical concepts.
- AI For Everyone by Andrew Ng (Coursera)
Artificial Intelligence is considered to be one of the more complex subjects in technology but its importance in our daily lives cannot be overstated. So, if you want your organisation to become better at using this technology, then this programme is worth a look. During classes, you will learn the meaning behind basic and crucial terminologies, what AI can and cannot do, spot opportunities to apply AI solutions to problems in your organisation, and more. By the end of the lectures, you will be proficient in the business aspects of AI and apply it aptly in relevant situations. The course is created by Andrew Ng, the pioneer in the field of artificial intelligence and the founder of Coursera.
USPs
- Understand what it is like to build machine learning and data science projects.
- Work with an AI team and build a strategy for your company.
- Navigate ethical and societal discussions relevant to this field.
- The lessons do not require any prerequisites; hence the course can be taken by anyone with any level of experience.
- The deadlines of the classes can be adjusted as per your convenience.
- Artificial Intelligence Certification by Columbia University (edX)
Enrol in this certification to gain expertise in one of the fastest-growing areas of computer science through a series of lectures and assignments. The classes will help you to get a solid understanding of the guiding principles of artificial intelligence. With equal emphasis on theory and practical work, these lessons will teach you to deal with real-world problems and come up with suitable AI solutions. This certification will give you an edge at job interviews and open up other opportunities for you.
USPs
- The videos guide you through all the fundamental concepts, beginning from the basic topics to more advanced ones.
- Applies the concepts of machine learning to real-life challenges and applications.
- Thorough instructions are provided for configuring and navigating through the required software.
- Work on designing and harnessing the capabilities of the neural network.
- The classes are divided into four parts along with relevant examples and demonstrations.
- Apply the knowledge gained in these lectures in an array of fields such as robotics, computer vision and physical simulations.
- An Introduction to Artificial Intelligence by IBM (Coursera)
This introductory course will guide you to the basics of artificial intelligence. With this course, you will learn what AI is and how it is used in the software or app development industry. During the course, you will be exposed to various issues and concerns that are relevant to AI like ethics, bias and jobs. After completing the course, you will also demonstrate AI in action with a mini project that is designed to test your knowledge of AI. After finishing the project, you will receive your certificate of completion from Udacity.
USPs
- Learn and understand concepts linked to AI, machine learning, deep learning and neural networks.
- No prior knowledge of programming or computer science is required to enrol in this course.
- Get advice from experts about learning AI better and on how to start a career in this fast-evolving field.
- Become eligible to enter other classes and programmes like AI Foundations, and the IBM Applied AI professional certificate after finishing this course.
- A 100 per cent flexible course with no deadlines and the freedom to study at your own pace.
- Microsoft Professional Certification in Artificial Intelligence (edX)
This programme focuses on helping you gain the skills needed to build deep learning predictive models for AI. While you are free to take the lessons in any order, it is advised you follow the suggested format so that you can develop your knowledge with gradually advanced concepts. After the completion of the first eight mandatory courses, you can choose from four options for the ninth one, prior to getting started with the capstone project.
USPs
- Learn to use Python to work with data.
- Understand the ethical practices in AI.
- Build ML and reinforcement learning models.
- Develop applied AI solutions and apply them.
- The programme is divided into nine courses along with tips, techniques and assessments.
- The final project gives you the chance to integrate the topics covered in the lectures and build optimal solutions.
9.TensorFlow for Artificial Intelligence by deeplearning.ai (Coursera)
If you are a software developer or have some prior experience with coding and are looking forward to building on those skills, then this certification is worth a look. These classes show you the techniques to implement the foundational principles of ML and DL using TensorFlow to build scalable models to solve real-world problems. By the end of this programme, you will have the practical skills to come up with scalable solutions for these problems as well as apply for relevant jobs.
USPs
- This course can be taken by anyone who has prior experience of Python.
- The instructor helps you to work with the fundamental features using examples.
- Students build a basic neural network and train it for a computer vision application.
- Understand how to use convolutions to improve your neural network.
- The training consists of tips and techniques along with assessments.
The Best Machine Learning Certifications [2020]
- Machine Learning Certification by Stanford University (Coursera)
This is one of the most sought-after certifications out there because it is taught by Andrew Ng, former head of Google Brain and Baidu AI Group. For a ML certification course to receive a rating of 4.9 out of 5 is no mean feat and the fact that it is associated with Stanford University simply adds much more credibility to the programme. The topics that are covered include supervised learning, unsupervised learning and best practices in machine learning. The programme structure is based on multiple case studies and applications to help you learn how to apply algorithms to build smart robots, text understanding, medical informatics, database mining and other areas.
USPs
- One of the best courses to begin learning the ML concepts and techniques used in daily work life.
- Get a broad introduction to ML, data mining and statistical pattern recognition with all the necessary topics.
- Learn some of the best practices in innovation that are inspired by Silicon Valley, pertaining to ML and AI.
- Learn to apply learning algorithms for developing smart robots, test understanding, computer vision, audio and other areas.
- Get access to multiple video lectures, guides, notes and practice exercises to boost your knowledge of ML.
- Earn a professional certificate that can testify your skills to employers.
- Machine Learning: From Data to Decisions (MIT Professional Education)
Participants will gain a practical understanding of the tools and techniques used in machine learning applications. In the MIT tradition, you will learn by doing. There are no prerequisites in terms of math or computational science, although a basic understanding of statistics is helpful. This is not a coding course, but rather an introduction to the many ways that ML tools and techniques can help make better decisions in a variety of situations.
USPs
- On your journey through this course, you’ll be in good company. Past participants come from a wide range of industries, job functions and management levels.
- This online programme approaches ML through the lens of practical applications. It is designed specifically for professionals who want to develop a competitive edge by turning what is unknown into what’s known — leading to better decisions and outcomes.
- Upon successful completion of the programme, MIT Professional Education grants a certificate of completion to participants.
- Machine Learning with TensorFlow on Google Cloud Platform
With over 2.5 quintillion bytes of data being generated around the world on a daily basis, it is safe to say that data is power. Comprising five courses, this specialisation begins with an overview of the importance of ML, before moving to lectures about building ML models. The programme starts with introductory-level lessons that cover what ML is capable of and why it is so popular, followed by classes that focus on TensorFlow, an open source ML framework. These sets of lectures aim to help you to create, train, deploy ML models; solve numerical problems, and much more. There are also numerous hands-on opportunities to enhance the accuracy of ML using the various features available on the Google Cloud Platform.
USPs
- From an introduction, to machine learning concepts, to what kind of problems it can solve, you will learn everything with this course.
- Learn how to create distributed ML models that scale in TensorFlow, and how to scale out the training of those models.
- Learn how to integrate the right combination of parameters that harvest accurate, generalised models, and gain knowledge about the theory behind the practices.
- Boost your skills and improve your learning with hands-on labs available with the Google cloud platform.
- Machine Learning Data Science Certification from Harvard University (edX)
This programme comprises nine courses that include machine learning, R, probability, linear regression and much more. This comprehensive programme is one of the best rated on the subject, online. You will also learn about inference and modelling, productivity tools and wrangling. This will be followed with a capstone project that you will create based on guidelines and have it assessed. The course is taken by Rafael Irizarry, professor of Biostatistics at Harvard University.
USPs
- Learn fundamental R programing skills, statistical concepts like modelling, inference and how to apply these in practice.
- Get knowledge and experience with tidyverse, including data visualisation with ggplot2 and data wrangling with dplyr.
- Develop an essential skillset for R programming, data visualisation, file organisation with UNIX/Linux and reproducible document preparation.
- Access motivating case studies, ask specific questions and learn by answering these questions via data analysis.
- Get in-depth knowledge of fundamental data science concepts via video lectures and case studies.
- Receive a professional certificate once you complete the course with given projects and exams.
- Machine Learning – Data Science Certification from IBM (Coursera)
If you have decided to pursue a career in data science or ML, then this is a fairly good place to begin. This ML certification consists of a series of nine courses that help you to acquire the skills required to work on industry projects. The lectures cover a wide range of topics including data visualisation, analysis, libraries and open source tools. By the end of the programme, you will have completed multiple assignments and projects to showcase your skills and enhance your resume.
USPs
- An introductory course focused on teaching individuals about ML and data science concepts with basic computer knowledge.
- Learn from some of the best industry professionals who have been working with IBM for a long time.
- Get access to multiple video tutorials, practice exams and quizzes to prepare yourself for the final exam.
- Get 24/7 support from a team of experts who will help you at every stage during the course.
- Receive your certificate of completion once you complete the hands-on projects and the given assignments.
- Hundred per cent flexibility, with the freedom to study from your comfort zone.
- Mathematics for Machine Learning (Coursera)
This course aims to help you to build a solid foundation in the underlying mathematics of ML, gain an intuitive understanding of the topic and use it in the context of ML and data science. Start with linear algebra and multivariate calculus before moving on to more complex concepts. By the end of the classes, you will have a strong mathematical footing to take more advanced lessons in ML and become a professional.
USPs
- Consists of three different courses, each focused on preparing you for different concepts of mathematics.
- Learn linear algebra, how it relates to data, and how you can work with vectors and matrices.
- Learn how to optimise fitting functions to get good fits to data with the help of multivariate calculus.
- Gain the prerequisite mathematical knowledge to continue your journey and take more advanced courses in ML.
- Learn from and get guided by a team of expert instructors who will also help you with any queries related to the course.
- Coursera Machine Learning Certifications (Coursera)
Individuals who are confused about where to start their ML journey can take help from these courses provided by Coursera. All these courses and classes are designed and reviewed by experienced professionals of top-rated universities around the world. These courses focus on creating systems to use and learn from large sets of data, so you will cover a wide variety of topics during the classes. Also, if you already have some basic knowledge of ML, then you can begin with the intermediate or advanced courses.
USPs
- Covers a wide variety of topics like predictive algorithms, natural language processing, statistical pattern recognition, and many more.
- Enrol in Master’s degree programmes if you want to earn a professional degree in ML.
- Get access to valuable resources, videos, articles and other downloadable resources to learn to the maximum extent possible.
- Practice your skills and improve your experience with the help of quizzes, practice exams and video tutorials.
- Some of these courses are absolutely free to enrol in, but you may have to pay some hidden costs.
