Online Machine Learning Courses & 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. 

The Imperial College of London offers the Getting Started With TensorFlow 2 online course in conjunction with Coursera. Achieving certification in courses offered by this esteemed institution gives you an inclusive educational experience and superior digital technology. 

The Getting Started With TensorFlow 2 certification course has modules spread out over five weeks, which candidates can complete in approximately 26 hours. Dr Kevin Webster, a Senior Teaching Fellow in Statistics at the Imperial College London, instructs the certification course. 

An intermediate-level course, the Getting Started With TensorFlow 2 training will teach you the fundamentals concepts of TensorFlow. You will become fully adept in developing deep learning models and using them to evaluate, train, and make predictions. 

Furthermore, the Getting Started With TensorFlow 2 certification course promotes interaction and improvement of one’s core abilities with a comprehensive curriculum and intermittent assignments. You can self-assess through these mediums and grasp the course contents at your own pace. Finally, Coursera awards you with a certificate upon successful completion. 

The Machine Learning Rapid Prototyping with IBM Watson Studio certification course will be allowing the students to work in the emerging technologies of AI. The syllabus is included in the online course Machine Learning Rapid Prototyping with IBM Watson Studio by Coursera. The online programme is  100% online programme and the course is having a duration of eight hours. The Machine Learning Rapid Prototyping with IBM Watson Studio certification syllabus includes the chapters of- Classification Prep Demo, Regression Prep Demo, Multi-armed Bandit Approach, Demo Classification: Making Changes to the Models, Automated Data Preparation, DAUB Algorithm, The model selection problem and others.

Machine Learning finds widespread application in providing recommendations and making better predictions in software by deploying opinions from users and constructing a model automatically while eliminating the need to consider all the details of that model. Advanced Recommender Systems Certification by Coursera will expose learners to advanced machine learning techniques that can be used to create sophisticated recommender systems. 

Offered by EIT Digital and Politecnico di Milano, both of which are top-ranked in their respective domain, this course boosts one's creativity and innovation skills and implores them to think beyond the thinkable. Advanced Recommender Systems Certification Syllabus will deal with the management of hybrid information and a combination of various filtering techniques. This course will ensure that learners derive the best from each approach taught to them.

At the course conclusion, candidates will have been well acquainted with factorisation machines and how to represent input data accordingly. They will learn all the essential methods that can be used to solve the cross-domain recommendation problem. Finally, identifying new challenges and trends in giving recommendations for numerous innovative application contexts will also be highlighted in Advanced Recommender Systems Certification Course.

End-to-End Machine Learning with TensorFlow on GCP is the successor of the first course Advanced Machine Learning with TensorFlow on Google Cloud Platform Specialization. This programme is included in a 5-course specialization that focuses on the topics of advanced machine learning that uses Google Cloud Platform. This course would give real-life experience by improving, establishing, and measuring production.

Through this course, the candidates would learn to build innovative, correct, and manufacturing-ready models for organised data, time series, natural language text, and image text. The course will end on recommendation systems. This programme does not have any schedule adherence; the candidates can look at the study materials according to their availability.  Along with theoretical concepts, the candidates would also learn about the practical approach of advanced machine learning.

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.

The Mathematics for Machine Learning: Multivariate Calculus course provides a brief introduction to multivariate calculus which is necessary for constructing several popular techniques for machine learning. The aim of the course is to provide an intuitive understanding of calculus, as well as the language required to look up concepts when candidates get lost. Candidates can still come away with the courage to dive into some more oriented machine learning courses in the future without going into too much detail. 

The Mathematics for Machine Learning: Multivariate Calculus course is the second one of the 3 courses in mathematics for machine learning specialisation. The goal of this specialisation is to bridge the gap then bring candidates up to speed in the underlying mathematics, develop an intuitive understanding, and relate it to data science and machine learning. The specialisation is pointed at what linear algebra is and how it applies to data in the first course on Linear Algebra. It will then draw attention to what exactly are matrices and vectors and how one can operate them. 

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. 

The Deep Neural Networks with PyTorch certification course will teach candidates, how to use Pytorch to create deep learning models. It is a part of the IBM AI Engineering Professional Certificate. There are a total of 6 courses in that specialisation. The Deep Neural Networks with PyTorch training course is the fourth one of them. Artificial intelligence or AI is revolutionising whole industries by transforming the way businesses exploit knowledge to make decisions across sectors. Organisations need skilled AI engineers who use cutting-edge approaches such as machine learning algorithms and deep learning neural networks to provide their companies with data-driven actionable intelligence in order to remain competitive. This Technical Certificate of 6 courses is designed to equip candidates with the tools which are needed to excel as an Artificial Intelligence or Machine Learning engineer in their career. 

Using programming languages such as Python, candidates will master the basic principles of machine learning and deep learning, which includes supervised and unsupervised learning. Candidates will also obtain a digital badge from IBM acknowledging their proficiency in AI engineering in addition to receiving a Technical Certificate from Coursera.

The course Fundamentals of Reinforcement Learning certification course is offered by Coursera by collaboration with the University of Alberta to make the aspirants skilful with machine learning and applications of Artificial Intelligence. The course is free to enrol and can access all the course materials free of cost. Therefore aspirants can use the opportunity for growing their career with a course completion certificate and increase the chances of hiring.

With the digital connection over the world, Business Intelligence over decision making is made essential in organizations. Decision making increases the prosperity of the business. Therefore the use of decision making with Artificial Intelligence and machine learning became most popular when the programme comes into existence. Organizations are looking forward to candidates who are skilled in this type of Artificial Intelligence, Robotics, Machine learning and, the Internet of things (IoT) as well

Coursera is the digital platform to learn the concepts that are offered for free. Candidates can learn throughout their lifetime and can avail of certificates after completion of the Fundamentals of Reinforcement Learning Training course. 

The Machine Learning for Computer Vision training is a 2-week online certificate programme offered by PDPM IIITDM Jabalpur. The programme aims to imbue you with essential machine learning skills, especially in the context of computer vision. 

The Machine Learning for Computer Vision course syllabus focuses on both theoretical and practical aspects of machine learning. During the course, you will learn concepts like supervised learning, unsupervised learning, feature extraction, image classification, deep learning, and much more.

Moreover, the Machine Learning for Computer Vision programme also features dedicated online lab and training sessions to help you develop the necessary practical expertise required in the industry. The course content will be delivered online, which you can attend from the comfort of your home.

The Machine Learning for Computer Vision certification programme also has a discussion forum wherein you can engage with your peers and talk about research problems and internships.

Machine Learning With Big Data is an online certification programme administered by the University of California San Diego to help the students explore machine learning with big data concepts. Machine Learning With Big Data  Certification Syllabus, developed by Mai Nguyen, the Lead for Data Analytics, and Ilkay Altintas, the Chief Data Science Officer, will give the students a clear understanding of strategies of machine learning for the analysis and exploration of data. 

In the Machine Learning With Big Data Certification Course, administered by  Coursera, the candidates will learn to build machine learning models with numerous algorithms and tools as well various concepts of big data. Machine Learning With Big Data Certification by Coursera is the fourth in six programmes of the Big Data Specialization. 

The Managing Machine Learning Projects certification course is a lunch of Duke University’s Pratt School of Engineering, and Coursera. This is course number 2 of the main AI Product Management Specialization programme. The course has a main focus on the practical aspects related to the management of projects in machine learning.

The Managing Machine Learning Projects training will take around 18 hours to get completed. This Coursera programme will walk every participant through different processes like data collection, building of a model, data collection, deployment, and maintenance of the systems of production. Apart from the above the candidates will also be taught processes in data science so that decision making in ML systems can be easier. 

Guided Tour of Machine Learning in Finance is offered by Coursera for intermediate-level students and learners to know the application of machine learning in finance. The online programme is the first programme in the Machine Learning and Reinforcement Learning in Finance Specialization offered by New York University and the Guided Tour of Machine Learning in Finance Certification Course can also be taken as a separate single programme. 

Provided by Coursera, Guided Tour of Machine Learning in Finance Training will shed light on machine learning and the application of ML to cope with various financial problems. Though the Guided Tour of Machine Learning in Finance Certification by Coursera is offered for intermediate learners, it is very needed for the learners to have an understanding and experience of Python, linear algebra, basic probability theory, and basic calculus to successfully complete the assignments. 

Machine Learning: Clustering & Retrieval is the University of Washington-offered online certification programme. The online course will expose the students to the practical understanding of clustering and retrieval aspects of machine learning through the case study of Finding Similar Documents. Machine Learning: Clustering & Retrieval Certification Course facilitates the students to take the course completely in online mode from anywhere in the world. 

Provided by Coursera, Machine Learning: Clustering & Retrieval Certification Syllabus will discuss the similarity-based algorithms for retrieval,  latent Dirichlet allocation (LDA), clustering, and the implementation of expectation maximization (EM) and the like. Machine Learning: Clustering & Retrieval Certification by Coursera is the fourth and last course in the Machine Learning Specialization. 

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. 

The Managing Machine Learning Projects with Google Cloud certification course is designed as a beginner level programme. The programme can be joined from the platform of Coursera. It offers a self-paced learning experience and students can learn from the available study material without any restrictions. 

The programme does not charge any amount for joining and learning from the course. Participants will be able to complete the whole Managing Machine Learning Projects with Google Cloud certification syllabus in approximately fourteen hours as it contains eight modules that will take up to a month. Students will be able to gain information regarding machine learning with respect to business problems. 

Students will be able to obtain a certificate if they complete the Managing Machine Learning Projects with Google Cloud programme within the given time. Candidates have the option to reset the deadlines according to the schedule of their suitability. The course also includes quizzes, readings, discussions, and assignments in order to provide a better learning experience for the students. The topics included in the Managing Machine Learning Projects with Google Cloud certification can be completed in the duration of one to three hours. 

Machine learning and artificial intelligence are new technological steps that can be applied in numerous fields to bring innovative breakthroughs. Machine learning and artificial intelligence has also an extraordinary scope and application in the medical and healthcare field. Fundamentals of Machine Learning for Healthcare will help the students to understand the significance of machine learning and artificial intelligence in the medical field and their potential to bring about transformations. 

Fundamentals of Machine Learning for Healthcare Certification Syllabus will introduce the learners to the basic concepts of machine learning and its applications in medicine and healthcare. By taking the course offered by Stanford University, the students will learn healthcare, health policy, pharmaceutical development, data science, and many more. 

Fundamentals of Machine Learning for Healthcare Certification Course, administered by Coursera, is a beginner-level programme that can be taken by the candidates at their own pace. Fundamentals of Machine Learning for Healthcare Certification by Coursera, instructed by Matthew Lungren who is the Associate Professor at the Department of Radiology, and Serena Yeung who is the Assistant Professor at Biomedical Data Science, is the third course in AI in Healthcare Specialization. 

The Machine Learning for Data Analysis certification course is a 1 week course taught by Wesleyan University, and Coursera. If students want to learn about predicting outcomes of the suture with data available today then this Coursera course is the best option that they can avail. The process of machine learning taught through this programme will help in testing, then applying, and finally applying algorithms that are predictive for achieving different kinds of goals. 

The Machine Learning for Data Analysis training is course 4 of 5 of the main Data Analysis and Interpretation Specialization programme. After this course gets completed, the candidates will be learning ways of interpretation algorithms of machine learning. These concepts will be serving as alternative methods that will help in giving answers to research questions.

Large volumes of data are routinely collected in today's scientific and economic industries. Making informed decisions requires the ability to analyze data and learn from it. Machine Learning using R enables the visualization of data, the execution of statistical tests, and the application of Machine Learning algorithms. R and Machine Learning Fundamentals online course teach how the artificial intelligence branch requires minimal human interaction and how the AI system gathers knowledge from data, detects patterns, and makes decisions.

R and Machine Learning Fundamentals certification course is presented by TCS iON in collaboration with Packt Publishing Ltd is a British educational company that aims to provide skill development training to working people. R and Machine Learning Fundamentals online training include 2 hours of thorough video lectures spanning 12 separate modules covering subjects such as data types, subsetting, control structures, data visualization with R, supervised and unsupervised machine learning, and many more.