List of Online Courses and Certifications

The Introduction to Machine Learning certification course is offered by Duke University. It will help you know your strengths and apply your skills in the most efficient manner to get work done. It will give you additional knowledge that will make you more confident in your work and perform better at your workplace or start your own business. 

The course will give you a brief overview of machine learning models like natural language processing, logistic regression, convolution neural networks, and multilayer perceptrons, while also explaining how these models can be put to use for solving technical problems in various industries like medical, image recognition, and text prediction. 

It is a combination of practical as well as theoretical knowledge about Machine learning, that will provide you with a framework for understanding how you can implement data science models and machine learning algorithms. The  Introduction to Machine Learning Training Course will allow you to work on a real-world hands-on project that is required in the fast-developing technological world. 

This course is offered by the University of Washington which is one of the oldest state-supported universities for higher education and one of the best research universities in the world. This course will help you know your strength, apply your analytical skills, and provide you with the confidence to perform efficiently at your workplace or start your own business. 

Students are introduced to the basics of programming languages and with additional focus on functional programming, using languages like ML, racket, and Ruby to teach the ideas to the student community, but the course aims to make students learn about how they can fit together any language to make an effective program in any language and learn new ones.

This course combines programming specifics and theoretical knowledge about the programming languages, providing a framework for understanding how a language can be used to create programs in an effective manner. This will demand you to put your analytical thinking to use, more, by selecting different languages as compared to in terms of the particular syntax of one language.  For learning how to write a robust, reusable, composable, and elegant program, it is very essential to learn about functional programming which offers the most important ideas in the latest languages. 

The Reinforcement Learning System (Capstone) certification course is a part of the ‘Reinforcement Learning Specialisation’ programme available on Coursera. This course is the 4th and final course in the series and aims to provide the students with complete practical knowledge on how to carry out Reinforcement Learning solutions in the real world.

In the Reinforcement Learning System (Capstone) online course, students will gain well-rounded and application-based skills that will help them in implementing Reinforcement Learning. They will complete the entire Reinforcement Learning problem-solving process – starting with the formulation of a problem, assessing the appropriate algorithm for the problem, and validating the impacts of the algorithm.

The Reinforcement Learning System (Capstone) programme by Coursera is suited for anyone who is expected to perform RL solutions in their field, along with the knowledge of skills like Machine Learning and Reinforcement Learning. The candidates will delve deep into the formalisation of a problem and how to translate it into an MDP. Finally, they will submit their Parameter Study towards the end of the course.

The Practical Reinforcement Learning programme by Coursera is the fourth out of the seven courses included in the ‘Advanced Machine Learning Specialization’. Offered by the National Research University- Higher School of Economics, this online programme will make you an expert in the field of machine learning.

Reinforcement Learning is one of the fundamentals of machine learning. Without getting a good grasp of this particular area, one cannot master the art of artificial intelligence. With the certification course in Practical Reinforcement Learning by Coursera, you can get in-depth knowledge about Reinforcement Learning and hone the various skills required to master this area of machine learning.

The Practical Reinforcement Learning online course by Coursera is well equipped with a planned curriculum as well as offerings like graded quizzes and assignments, peer feedbacks, practice quizzes, etc. that will help you to become proficient in this field. You will earn a shareable certificate upon completion as well.

The Practical Reinforcement Learning online programme by Coursera is a full package that covers all the core concepts of Reinforcement Learning, including free methods, dynamic programming, value-based methods, neural networks, algorithm-writing, model-free methods, and more.

The workforce of the future requires new skills and abilities to thrive. Revolutionary developments in technology have transformed the way we do business, communicate, and live. The edX Future of Work: Preparing for Disruption certification course is designed to help you study how automation, novel businesses, AI, and technological innovations are changing things worldwide.

Numerous repetitive, low-skill and routine jobs are on the verge of extinction due to Machine Learning, AI, hyper-connectivity, and automation. So, the Future of Work online programme by edX teaches you how this creates new possibilities like enhanced delivery of services, enhanced productivity, and the creation of new types of jobs.

The Future of Work: Preparing for Disruption course emphasises the need to create skilful human resources for the upcoming era. It is the only course which investigates the World Development Report (WDR) of 2019. You will understand how developing nations have to develop human capital to keep up with rapid innovation across the globe. There are two options for learners to enrol in the online programme; verified and audit modes. In the audit-free mode, the candidates can access the programme only for a limited period.

The Deep Learning Essentials program by edX will help candidates discover the issues of discrimination and bias in Machine Learning and gain valuable insights regarding the subject. They will become adept at performing tasks like signal processing, computer vision, robotics, sequential decision-making, and natural language processing.

Besides, the University of Montreal offers the Deep Learning Essentials training which is designed by IVADO, a hub of scientific and economic data science and Mila. The scientific director of this course is Yoshua Bengio, a reputed expert in artificial intelligence and a pioneer in Deep Learning, who is also a professor at the University of Montreal.

Rife with video tutorials, tests, and assignments, the Deep Learning Essentials certification course also provides diverse learning tools to help candidates become adept in deep learning's fundamental concepts and methods. 

On successful course completion, candidates can also secure a verified certificate from edX to acknowledge their newly acquired knowledge in the field. The candidates may choose from any one of the tracks available namely verified and audit to complete the programme. Both the tracks are self-paced but during the audit track, the candidates shall receive limited period access to the course. On the other hand, the verified track will offer unlimited time for accessing the course.

Machine Learning with Python: A Practical Introduction Certification Course will explore many popular and modern algorithms including Classification, Regression, Clustering, and models such as Train Split, Root Mean Squared Error (RMSE). Also, students will look and learn from genuine and authentic examples of machine learning and see how it affects society in ways you may not have speculated. 

Machine learning from the past few years has become an integral part of many commercial applications, software and research projects, yet this field is not exclusive to huge companies and organizations with extensive research teams. If you start to use Python language, even as a beginner, this short-term course will teach you practical ways to write and build your own machine learning solutions and machine learning applications are limited only by your imagination.

The Machine Learning with Python: A Practical Introduction Classes will be useful for the students to create products that parse, reduce, simplify and categorize computer data, and then extract actionable intelligence from that data. Machine Learning with Python: A Practical Introduction Certification Course is offered by EdX in association with IBM. There are two options for pursuing the self-paced programme; verified and free. In the verified mode, the learners can take the self-paced course by paying the fee and get unlimited access and in the free mode, they can audit it for a limited duration. 

Analyzing Data with Python certification course is designed by IBM and taught by Joseph Santarcangelo - PhD., Data Scientist at IBM, which is delivered by edX, which is targeted at the students looking for a comprehensive learning environment that could assist in their mastery of the concepts and methods required to develop the skills necessary for analyzing data with the Python programming language. Students who are interested in enrolling in the Analyzing Data with Python online classes by IBM and edX should be familiar with the fundamentals of programming in Python.

Analyzing Data with Python online training is a 5-week learning program that includes approximately 2-4 hours of extensive video-based materials that cover topics such as data loading, data manipulation, data preparation, data cleaning, linear regression, data visualization, ridge regression, polynomial regression, and machine learning models. Students who successfully finish the verified version of this program will also receive a skill badge that validates their knowledge and skills. This self-paced programme free course and they learners can upgrade it to the verified mode and get certification by paying the course fee. 

The Fundamentals of TinyML Training Course is an open course provided on the HarvardX platform coordinated by edX and Harvard University. The course will introduce students to the fundamentals of embedded systems and machine learning along with the core aspects of TinyML language.

The Fundamentals of TinyML Certification Syllabus will benefit students who are interested in data analysis and statistics. The course is an introductory level course that requires students to have knowledge about basic scripting techniques in Python. The course is supported by online study materials and instructed by Vijay Janapa Reddi and Laurence Moroney.

The Fundamentals of TinyML Course is taught over 5 weeks in a self-paced manner. The course focuses on the main aspects of deep learning, machine learning, and embedded devices and systems, like smartphones and other devices. Upon the successful completion of the online exams and assignments, students will receive a certificate if they choose the verified mode with the course fee. In the free mode, they can audit it for a limited period. 

The Deploying TinyML Certification Course is an open online course that introduces students to the steps involved in implementing TinyML applications. The course will help students understand the workings of the software along with the right codes required to deploy their tiny microcontroller-based device. It is a specialized course and a mix of computer science and electrical engineering.

The Deploying TinyML Training Course is an intermediate-level course that requires learners to have basic knowledge of the Applications of TinyML and Basic Programming in C/C++. The course taught in a self-paced manner will be beneficial for students who wish to earn a professional certificate in Tiny Machine Learning.

The Deploying TinyML Online Course is taught over 5 weeks with the aid of online course materials. The course is instructed by Vijay Janapa Reddi, Professor at Harvard University and Pete Warden, Technical Lead at Google. After the completion of the online assessment process, students will get access to a certificate in the paid verified mode. In the free audit mode, they can get a limited duration of access to the self-paced course. 

The Managing Big Data With R and Hadoop training is a five-week training programme offered by the FutureLearn portal in association with the Partnership for Advanced Computing in Europe (PRACE). In this course, candidates will learn about statistical learning, the use of Linux with Hadoop, and how to manage data using different tools and techniques such as R, Hadoop, and R Studio. Also, learners will learn to use the big data Hadoop tool to manage and analyse big data for the organisation or client.  

Managing Big Data With R and Hadoop online course will be taught by Janez Povh, Biljsna Mileva Boshkoska, and Leon Kos using the English language as a medium of teaching. This course is designed for people who are interested in learning about data science, computational statistics, and machine learning. To apply for this course, students will have to visit the official website of the provider and register for the Managing Big Data With R and Hadoop online course. As for the complete information about this course, please go through the article given below.

Online Certificate Course in Deep Learning using Tensorflow 2 and Keras by the National Institute of Electronics and Information Technology is a foundational course aimed at imbuing within students various Deep Learning skills and algorithm evaluation performances for multiple applications. It touches on machine learning, natural language processing (NLP), and programming languages that guarantee a career in AI.

The course is spread across five weeks and filled with several theory and practical learning modules. Moreover, the Online Certificate Course in Deep Learning using Tensorflow 2 and Keras by NIELIT also covers Cloud Computing, Internet of things (IoT) and Data Analytics. It includes case studies and projects which are industry-relevant. A course completion certificate is also provided to candidates towards the end of the programme.

Mr Ripunjay Singh is the instructor of NIELIT’s Online Certification Course in Deep Learning using Tensorflow 2 and Keras programme. Candidates need to dedicate one hour on weekdays from 3 PM to 4 PM. Candidates are selected on a first-come, first-serve basis.

The Online Hands-on Machine Learning and Artificial Intelligence Program is a no-coding, no-programming course. But it is still totally lab-oriented, practical, and interactive. It aims to study analytics techniques using Machine Learning and enable students to employ it in their research, teaching, or other industrial contexts.

KNIME and H2O are the two tools you will learn to use with the Hands-on Machine Learning and Artificial Intelligence programme. The instructor will explain each step in a particular project/assignment and create a workflow for it on KNIME. You will then go through the steps and try to solve them yourself on your laptop. Whenever you have a doubt or question, you can ask the instructor in real-time. The results will become available to both you, and the instructor immediately afterward.

The Hands-on Machine Learning and Artificial Intelligence training sessions will go live between 2 PM and 5 PM on weekends. There will be six hours of training each week for five weeks, a total of 30 hours. Esteemed faculty from the Indian Institute of Technology (IITs) from across the country teach students the course.

The Using Machine Learning in Trading and Finance online course is providing a platform for the students to learn and study about the basics that are involved in developing advanced strategies that are used in modern machine learning techniques. 

In the online programme on  Using Machine Learning in Trading and Finance by Coursera, the applicants will be studying the key components that are common to all the trading strategies irrespective of the platforms and dimensions. 

In the Using Machine Learning in Trading and Finance certification syllabus, the enrolled students will be covering the comprehensive chapters of-  Regularization: L1, L2, and early stopping, Regularization: dropout, Lab Intro: Keras functional API, Regularization: the basics, Neural networks with Keras functional API, Collect the data, Backtest on unseen data, Selecting a machine learning algorithm, Lab Intro: momentum trading, Creating features, Define the problem, Split the data and others.

The PyTorch Basics for Machine Learning certification programme is offered by IBM to arm you with the skills for implementing classic machine learning algorithms. You will get to know how PyTorch is used to optimise and create deep learning models. 

During the PyTorch Basics for Machine Learning training, you will learn important models such as linear and logistic regression models. This introductory-level programme will teach you how to train your models and their related concepts like gradient descent, cost and loss.

With the learnings of edX’s PyTorch Basics for Machine Learning course, you will learn to save your training and model in apps like checkpoints, early stopping and cross-validation for hyperparameter selection. Also, basics around the linear object, like their interaction with data with a distinctive number of samples and different dimensions, will be cleared.

The PyTorch Basics for Machine Learning course also includes a final project in the end to assess your skills and performance. You can even get a paid instructor-signed certification after completing the course. The learners also can audit the self-paced programme without paying the fee for a limited duration. 

The Deep Learning on Azure with Python certification course is a five-week-long online programme designed to help you develop the critical skills required of a Machine Learning Engineer. You will understand the intricate workings of Deep Learning during this programme. You will also know about the Data Science skills needed to build Machine Learning (ML) models.

Throughout the Deep Learning on Azure with Python online programme offered by FutureLearn, you will explore how ML enables you to build complex systems. Also, you will know about its broad spectrum of applications, including medical diagnosis, self-driving cars, etc.

For building ML models during FutureLearn’s Deep Learning on Azure with Python online course, you will use Microsoft Cognitive Services on the MS Azure cloud platform. Python programming shall be used for this purpose. You will get hands-on experience and a thorough introduction to the field of Machine Learning with practical examples. Moreover, by obtaining the course certificate, you can prove to your future employers that you are job-ready and skilled in this field. 

A course in data science, the AI and Machine Learning Algorithms Using Python programme will provide you with a strong foundation in the theories of machine learning. You will learn through practical scenarios and experience the deployment of machine learning models. 

The AI and Machine Learning Algorithms Using Python syllabus will cover the core principles of AI technology like standard regression techniques and ML categories (unsupervised and supervised learning). You will also become adept at understanding how machine algorithms behave and learn.   

Additionally, you will receive practical experience by producing and deploying a machine learning model. This course will teach you how to use Azure Notebooks and Python to extract insights from ML models after they've been deployed. All this will be covered in a span of five weeks. However, you can study the AI and Machine Learning Algorithms Using Python certification programme at a pace convenient to you. Finally, you will receive a digital certificate on successful completion. 

A part of FutureLearn's Advanced and Applied AI on Microsoft Azure ExpertTrack; the Microsoft Future Ready certification course aims to help you prepare for the various Microsoft Microcredentials. This is a data science course that runs for five weeks. 

The Microsoft Future Ready certification syllabus has been divided into weeks, steps, and activities you can pursue at your own pace. During this course, you will gain industry-specific knowledge of Python programming and machine learning through theoretical as well as practical experience. 

You will become adept at developing, validating, and deploying different types of machine learning models in the Microsoft Future Ready course. This course will also help you understand complex data relationships using Python and Azure Notebooks to derive insights effectively. 

Besides, once you complete all the steps in the Microsoft Future Ready online course, you'll be eligible for a digital certificate to verify your machine learning knowledge and skills. 

The online programme on Microsoft Future Ready: Principles of Machine Learning with Python Programming by FutureLearn is a part of the ethic law and the process of implementing an AI solution on the Microsoft Azure ExpertTrack course. The course will be held for a duration of five weeks on the online platform.  Upon completing the syllabus the students will learn about the fundamentals of Machine learning and further learn the mechanisms of applying it in the real world domain. The students will be working on two tools namely- Azure and Python. The appearing students will also be working on real-world examples to develop their skills and practice.

Machine Learning (ML) is rapidly transforming the world. The Big Data Applications: Machine Learning at Scale certification programme is an advanced-level online course to provide you with comprehensive ML knowledge. During the course, you will explore what type of real-life problems can be solved with ML.

Offered by Yandex, the Big Data Applications: Machine Learning at Scale training by Coursera will equip you with skills to build ML models through practical assignments. You will also learn how to create your recommender system.

Throughout the Big Data Applications online training’s five-week duration, you will go through extensive reading material, practise exercises and quizzes. It will also include exclusive video lessons delivered by top-rated instructors.

Coursera’s Big Data Applications online course will educate you on the various applications of Big Data and ML. The skills you develop will enable you to undertake different kinds of pragmatic machine learning tasks. Upon course completion, you can also earn the coveted e-certificate, which is purchasable.

The ‘Natural Language Processing’ online certification course is provided for the eligible students to equip themselves with the advanced skills of NLP for everyday tasks, suggest outlooks, and identify the optimum techniques. This online free course is provided by Coursera online education platform and the curriculum is developed by the HSE University. The course duration is designed to be completed in thirty-two hours and the students are allowed to work with flexible deadlines.

The course instructors for this online training are academic and industrial professionals Anna Potapenko(Researcher), Alexey Zobnin(Associate Professor), Anna Kozlova(Team Lead), Sergey Yudin(Analyst-Developer), etc. This course is part of the Advanced Machine Learning Specialization and enables participants to learn using course content provided with subtitles in Arabic, French, Portuguese, Italian, Vietnamese, Korean, German, Russian, English, Spanish, and other practical learning methodologies.

The ‘Natural Language Processing’ online training program helps students receive a course certificate that is shareable online after finishing the course study, assessments, and tests.

Applied Data Science for Data Analysts is an online Databricks-offered programme designed for intermediate-level learners. The online certification is the final course in the three-course Data Science with Databricks for Data Analysts Specialization. Thus, to be eligible for taking the online programme, the learners must have completed the first two courses in the specialization. Applied Data Science for Data Analysts Certification Course, provided jointly by Coursera and Databricks, will help the learners to enrich their data science, and applied data science with python and machine learning skills and help the student to become masters of applied data science. 

The learners passionate about learning about apple data science can enrol and complete the Applied Data Science for Data Analysts Training within approximately 16 hours. As the Applied Data Science for Data Analysts Certification by Coursera is completely offered in the online mode, the candidates can opt for the programme at their convenience and pace from anywhere. 

The University of Alberta and Alberta Machine Intelligence Institute offer the Sample-based Learning Methods training programme in conjunction with Coursera. An intermediate-level course, the programme is spread across four weeks, with intensive modules on reinforcement learning. The course will also help you understand how learning from experience can help you attain optimal behaviour. 

The Sample-based Learning Methods certification course will help you understand concepts like Temporal Difference learning, Monte Carlo strategy, exploration, dynamic programming, and more. Moreover, the certification course will provide you with a chance to apply TD algorithms, Expected Sarsa, Q-learning, and more.

Instructors will conclude the Sample-based Learning Methods online course by looking at how algorithms can combine model-based planning and temporal difference updates to fast-track learning. Additionally, the certification course offers the flexibility to learn at your own pace in your own time and set your own deadlines. 

You will also receive a combined shareable certificate from the University of Alberta and Coursera, upon completion of the Sample-based Learning Methods course.

In the present times where the advances in technology have shifted to IoT (Internet of Things), the concept of Deep Learning can be foreseen as one of the crucial ones, to be understood and well researched. Deep learning is faster and easier to develop and deploy as well. The Introduction to Deep Learning & Neural Networks with Keras certification course, the participants will get a deep insight into the Deep learning models. Furthermore, they will also be able to create models of Deep learning by making use of the Keras library.

The entrant will be introduced to exhilarating applications of Deep Learning. They will be learning about various deep learning algorithms and neural networks which are inspired by the functioning of neurons and the brain with respect to data processing. They will also get an insight into the working of the neural networks to feed the data throughout the network.

The Introduction to Deep Learning & Neural Networks with Keras training will provide knowledge about optimisation of variables as per the defined function, gradient descent algorithm, backpropagation, and updating the weights and biases of neural networks. Furthermore, the entrant will be taught about the activation functions and vanishing gradient problems. 

Reinforcement learning is a machine learning method that helps to understand how the software agents should take actions according to the situations and requirements. Helps solve all the problems that have large or high dimensional and potential limitless spaces available. It helps one to investigate how policy prediction and evaluation methods like TD and Monte Carlo can be used to help function approximation settings. 

Prediction and Control with Function Approximation certification course by Coursera include features construction techniques for representational learning through a neutral network, RL and backdrop. This course is designed for the candidates who have completed the first and the second part of the reinforcement learning and specialization training as it is a continuation of the same.

By doing the Prediction and Control with Function Approximation training course they will be a field ready and gain knowledge that will help them master their skills and help upgrade their portfolio which will, in the end, help them towards their successful career. 

Amazon Web Services (AWS), the most comprehensive and vastly adopted cloud platform across the globe, is a fast, easy and cost-efficient platform to build ML applications. The AWS Machine Learning offers tools and services which cater for the developers and organisations to build ML models more efficiently. Globally, AWS Machine Learning is used by developers to build ML models that can test product designs, assess property damages, improve healthcare operations, analyse customer behaviour, fraud detection and much more.

Getting Started with AWS Machine Learning certification course is an online offered by AWS through the Coursera platform. This certificate programme will assist the participants to gain familiarity and working knowledge of AWS Machine Learning. The course content spreads over 5 weeks and includes module videos covering almost every significant aspect of machine learning. Participants will receive a shareable certificate upon completion of this online certificate programme.

This program on ‘Full Stack Applied AI Course’ is developed and designed by the data science institute for the candidates to transform into python professionals with AI and ML skills. The program is scheduled for four hundred hours and the candidates will be required to attend a total number of fifty classes in which they are allowed to explore the features of deep learning, machine learning, and data science within the scope of applied artificial intelligence to meet the business needs.

The learners will get hands-on experience with the software tools such as Python and other data science aspects. The ‘Full Stacked Applied AI online course’ curriculum is application-based and includes data extraction, wrangling statistical frameworks, supervised and unsupervised machine learning strategies that are required for various applications of AI. The assignments, case studies, projects, and evaluation helps the students upskill themselves with experimental industrial insights and gain a valuable certification.

With the increasing use of technology and machinery in our daily lives, people have started accepting and learning various methods and techniques. It has become essential to possess the skills and capabilities to beat the competition. Neural Network course certification online teaches various algorithms which enable pattern recognition.

The Neural Networks course by Jigsaw Academy online certification is a framework specially designed and conceptualized for candidates interested in learning advanced machine learning algorithms that can enable pattern recognition based on a large number of inputs. The Neural Networks course will provide a deep dive into the world of neural networks, make you understand the algorithms and techniques, and ultimately gives an insight into deep learning. 

Conducted by Jigsaw Academy, the Random Forest certification course is worth not missing pursuing. Imparting an in-depth understanding of different tools and technologies used in Random Forest, the one-month course is definitely worth going for. The course can be finished in an online mode within a month. Only those candidates who have a basic informational knowledge of topics like statistics, machine learning, and R can participate.

The Random Forest training has been designed and conceptualized by experts in this industry. With the growth and advent of technology, it is essential to stay abreast with current developments in this industry. Random Forest Certification course by Jigsaw Academy will give immense exposure to the candidates and help them in learning algorithmic machine learning methods and several other subjects. 

The changes in technology have really gone so far and reached higher day by day and with that, the use of kernel functions has begun developing at a higher rate too.  This Support Vector Machines certification course makes the standard of learning about the support Vector machines pretty easy. Support vector machines really help in understanding and solving the convex optimization process. 

Machine learning would be very easy after the completion of this Support Vector Machines training course. The support vector machine technique was brought in 1995. The revolution of vector machine study brought a big change in the industry of machine study. This Support Vector Machines programme by Jigsaw Academy is something worth not missing.