Online Machine Learning Courses & Certifications

In the Machine Learning Fundamentals certification course by edX using real-world problem statements students will learn to figure out the features of topics in the corpus, classify the given images, group people according to various profiles depending on their personality and also capture the semantic structure of words available. With the information learnt in the Machine Learning Fundamentals training, the students will learn to analyze different types of data and also they will be able to build predictive and descriptive models. The Machine Learning Fundamentals certification has the following included in its curriculum- conditioned probability, linear models, random forests, reduction, bagging, and many other topics that deal with the domain of machine learning. 

The examples that will be provided in the Machine Learning Fundamentals programme will be in the language of Python and will use Jupyter Notebooks. The candidates will also be practising various types of algorithms using data science and its applied tools. The Machine Learning Fundamentals online course will provide students with both discriminating and generative models. There are 2 tracks namely the audit track and the verified track into which the candidates may enrol. The candidates may access the course for a lifetime by paying a fee which is called the verified track, and the audit track asks for no fees but offers limited period access to the course.

Throughout this programme, the candidates will enhance their skills in machine learning and will learn to apply these skills to problems of the real world, related to the field of business. This online programme of Imperial Machine Learning for Decision Making is provided to the candidates through the platform of Emeritus and is brought to them by the Imperial College Business School. 

The participating candidates will gain exposure to analytical techniques, for example, regression, classification and clustering and learn how to apply these techniques to real-life issues arising in the field of managing a business. The students will be provided with opportunities to have conversations with experts who have deep technical expertise about the subject, which will ultimately help them in having a greater impact on the company they work in. 

This course is for a duration of 10 weeks wherein the students will not only be learning the theoretical know-how but also the practical applications of the concepts learnt.  

With machine learning and artificial intelligence gaining immense popularity, the skills of future-ready analysts, engineers, technologists, and data managers also must expand, shift,  and advance. Machine Learning: Fundamentals and Algorithms online course will provide you with ample technical knowledge and analytical methods to prepare you for the next gen of innovation.

Organised around 10 modules, the Machine Learning: Fundamentals and Algorithms course help you deepen and broaden your Python programming skills for ML applications. You can further apply this technical knowledge to the industry verticals currently integrating machine learning and AI into their digital drivers.

The Machine Learning: Fundamentals and Algorithms programme is designed for participants with Python programming experience who want to learn more about the underlying mathematics. Upon programme completion, you will receive a verified digital certificate from Carnegie Mellon University. 

Artificial intelligence and machine learning advances run hand in hand with the degree to which quantum computing footprint improves. Thus, it is natural to leverage machine learning capabilities with the advent of quantum computing. This Quantum Machine Learning certification course will explore the underlying principles associated with futuristic technologies. 

The program on Quantum Machine Learning encompasses the advantages of machine learning once it is coupled with futuristic quantum technologies. These have the potential to provide the much-awaited advancements of this industry. Some examples include machine learning and select frameworks in Python. 

This Quantum Machine Learning training program is intended to be delivered across 9 weeks along with an input of 6-8 hours per week by the participants on their own time for optimum results. The University of Toronto is the partner institution for this self-paced course. The video transcripts are in English and the students have an option to get a paid plus official certification. 

The candidates who enroll in any track of the course will be able to progress at their speed. Both tracks - audit and verified may be opted for by the candidates for finishing the course. If the candidates are interested in learning for free without a certificate they may choose the audit track which is open for a limited period of access. For unlimited access, the students should switch over to the verified track by paying some fees.

Machine Learning in Business by the Rotman School of Management, University of Toronto is a program that will make a data science team better and more proficient and give the data analysts the opportunity to traverse and communicate their language and mindset to their businesses which in turn will increase the chances of greater business benefits.

Machine Learning in Business being a subsection of Artificial Intelligence implements means that assist the data analyst in examining huge sets of data in every other field whether in healthcare or finance. This course is a thorough run-through to the candidates about machine learning and its numerous methodologies. 

This program ensures that candidates address the managerial doubts but at the same dive into the world of machine learning and learn the various consequences it can have on a business in the future. Machine Learning in Business program is designed to locate fast-growth areas of business via machine learning techniques which includes but is not limited to Support Vector Machines (SVMs) and Natural Language Processing (NLP).

The Machine Learning Foundation certification course is an online course of three-month live projects and six days or three weekends training that covers Python, machine learning algorithms, and deploying machine learning models. The whole Machine Learning Foundation training will take place via an online platform and the candidate will have complete access to that after enrolling in the course. The candidate can get Machine Learning Foundation certification at the end of the course accredited from IABAC. The complete curriculum of the Machine Learning Foundation certification syllabus is structured according to the emerging demand of the industries. 

The Machine Learning for Earth System Sciences certification course offers a comprehensive exploration of spatio-temporal statistics and data mining, focusing on their applications in earth system sciences. Intended for final-year undergraduates, postgraduates, and research students, it covers earth system observations, data analytics, and modelling in domains like hydrology and climate.

Prerequisites include mandatory machine learning knowledge, optional deep learning expertise, and a working understanding of earth system science domains. The Machine Learning for Earth System Sciences certification by Swayam caters to both undergraduate and postgraduate levels, fostering a solid grasp of statistical concepts in analysing earth system phenomena.

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The Practical Machine Learning with Tensorflow certification course offers a comprehensive curriculum that covers the key aspects of Tensorflow and Machine Learning such as data input, Tensorflow preprocessing, and prediction. This certification course lasts 8 weeks, and its prerequisites are Programming, Data Mining, Machine Learning, or Data Science. 

The students gain hands-on training in the subject from industry experts. The Practical Machine Learning with Tensorflow certification by NPTEL equips students with the required skills and knowledge to build ML models using Tensorflow. The candidates also learn the application of techniques, principles, and strategies in real-world projects.

Also Read: Online Machine Learning Courses & Certifications

The Machine Learning ML program focuses on the scientific discipline that is related to the genre of Machine Learning and helps the students to develop algorithms to help the students find patterns that are related to make predictions from the domain of empirical data. In the online course on Machine Learning, ML by Swayam, the students would be finding patterns or will be making predictions from the given empirical data. 

The certification program over the course of eight weeks will be focusing on the following- Forms of representation, Examples, demos and exam preparations, Learning enabled by prior theories, Tools and resources + cognitive science, and Machine learning-based artificial neural networks. The Machine Learning ML certification course will be benefiting the students to incorporate the knowledge of machine learning in real-world examples and tree-based inductive learning along with logic programming. The session will be making the candidates professionally ready.

Machine learning, which combines the areas of statistics, optimization, computing, and data mining, is being embraced across sectors due to its capacity to solve issues in the availability of large data sets. The Machine Learning: Practical Applications online course covers a wide spectrum of machine learning methodologies, with a focus on artificial intelligence in current business analytics.

Modern machine learning achievements include its use in commercial activities like recommendation systems (like Amazon and Netflix), search engines, and promotion. In financial companies, machine learning technologies are rapidly being utilized for algorithm-based trading, forecasting consumer behaviour, risk, and compliance. The Machine Learning: Practical Applications Training from the London School of Economics provides a systematic approach to artificial intelligence in current business statistics.

The Machine Learning: Practical Applications syllabus engages with real-world challenges by implementing various machine learning models to large datasets in R, interpreting the predictions, and evaluating these predictions to guide the business.

The Launching into Machine Learning programme is a part of the Machine Learning with TensorFlow specialisation, offered by Google Cloud. This Beginner-level online professional course takes about 14 hours to complete. The course of instruction in English and subtitles are also provided for ease of grasping. 

The Launching into Machine Learning online course is offered by industry-leading professionals who have had multiple years of work experience in Machine learning and Tensorflow. Thus, you can be assured of being trained by the best in class. Through this course, you will understand the essence of deep learning and how to optimise it to mitigate common problems in machine learning. 

The Launching into Machine Learning certification syllabus provides you with repeatable and scalable test datasets perfect for training and evaluation. Moreover, you will learn to evaluate the models through loss functions and performance metrics. What’s more, the flexible schedule allows you to learn at your own pace and convenience. 

The Coursera Probabilistic Graphical Models 3: Learning certification course covers probabilistic graphical models, commonly known as PGMs. They are a rich framework used for encoding probability distributions over complex domains. They form the foundation of state-of-the-art methods in different applications such as speech recognition, natural language processing, medical diagnosis, image understanding, and many more. They are also instrumental in formulating many machine learning problems. 

The Probabilistic Graphical Models 3: Learning training is the third course in a series of three. Where the first course focused on representation, and the second focused on inference and the final course helps in addressing questions related to learning. The course discusses the main problems of parameter estimation in both directed and undirected models. 

Moreover, students can receive a course completion certificate for the Coursera Probabilistic Graphical Models 3: Learning programme. Candidates can attach the certificate to their LinkedIn profile or their resume/CV.

Machine Learning using R Programming certification course is a certificate course offered by NIELIT Haridwar Campus. This course is an online program that will train the candidate to be competent with the fundamentals of machine learning and the basics of R language. The programming is taught as a part of the online course and is accessible from the comfort of a laptop or computer. The course spans a duration of 6 weeks. The first four weeks focus on topics related to certification and the last two weeks are dedicated to a project. 

The project is done without adding additional see connected from the participant. The certificate is awarded upon satisfactory performance of the candidate in the final exam test and minimum attendance percentage. The course has online assignments and content presented as e-content in the form of handouts for presentations. The Machine Learning using R Programming training course will cover the basics as well as dive into practical applications in machine learning.

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According to a Hackernoon report, 74% of decision-makers, corporate owners and IT executives believe machine learning has the ability to transform their work and sector. Companies that use machine learning to enhance organizational performance and improve the decision-making process have clear benefits over those that do not. The Machine Learning online course aims to provide candidates with the knowledge and skills needed to comprehend the effect of machine learning and effectively articulate its integration.

It has never been simpler for businesses of all sizes to leverage the value of data. Introduction open-source and free Artificial intelligence and machine learning technologies. Embedding machine learning technologies into an organisation effectively necessitates a practical grasp of its concepts. The Machine Learning training teaches about the various types of modelling concepts used in machine learning. The Machine Learning syllabus focuses on determining the models, methodologies, and ethical implications of machine learning techniques, as well as presenting an economic case for using them in the firm.

Machine Learning in Business certification is basically a 6 weeks small course designed by  MIT Sloan School of Management and the MIT Computer Science and Artificial 

Intelligence Laboratory (CSAIL)along with its content partner being GetSmarter. With this programme, candidates can learn about how machine learning can be capitalized on by businesses.

The Machine Learning in Business certification syllabus is divided into 6 weeks which is taught online, and it will help in answering questions related to machine learning which is a branch of Artificial Intelligence. Basically here the programming of Computer Science will be used to improve data performance in businesses.

Machine Learning in Business training is an online executive programme that is guided by the MIT faculty to help the participants understand the foundational level capabilities of Machine Learning along with its advantages and limitations so that its’ potential can be unlocked within businesses. This certification course will give an opportunity for designing a roadmap towards the integration of business needs with machine learning successfully.

The Introduction to TensorFlow certification course is thoroughly an online programme that is available for free for a specific period of time. The main focus of the programme is to make students aware of the Tensor flow. The training will revolve around the topics of datasets, designing and building of Tensorflow, and other features of the programme, etc. The course will take up to nineteen to twenty hours of learning.

The Introduction to TensorFlow online course is created for the students who want to learn from the course at their own pace so that they can take as much time as required to completely understand every topic. There are no last dates for the programme and it has no limitations with regards to attendance percentage or timings of attending the sessions.

The course provides an intermediate level of learning and requires no academic qualifications to get admitted into the course. Students also get an opportunity to become a certified user of the course and obtain a verified certificate when the Introduction to TensorFlow certification syllabus is completed by the participant. The language of the programme is set for English, however, participants who have a language barrier can use the subtitles that are available in Russian, Spanish, Portuguese (European), English, and French languages.

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.

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. 

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. 

Amazon Web Services (AWS) is offering the Amazon SageMaker: Simplifying Machine Learning Application Development certification course. It will act as your guide for using Amazon SageMaker for the integration of ML or machine learning into your apps. Machine learning has surfaced as one of the most sought-after technological domains in recent times. Thus, the course can help you develop your skill-set in just a span of 4 weeks.

The Amazon SageMaker online course by edX will empower you with the knowledge of training a model with the help of a Jupyter Notebook. You will learn under the able guidance of AWS Training and Certification expert educators. Furthermore, you will have the assistance of video lectures, hands-on exercises, and demos to help you achieve fluency in the course concepts.

Moreover, the Amazon SageMaker training will allow you to hone your prior skills and help you gain new ones. You will have improved career opportunities at hand after completing this course. Although it is free of charge programme, you need to purchase the Verified Certificate track to access graded assessments and the programme certificate.

Apply Creative Machine Learning certification is a month-long course that only requires a student’s 2 hours in a week time. Developed by UAL Creative Computing Institute, and Institute of Coding, this certification course can be found on the FutureLearn platform. Among all the industries, machine learning is actually causing a revolution in the creative industries ranging from Music to Photography.

Apply Creative Machine Learning certification syllabus is all about the concepts that come under IT, and Computer Science. Any technology we use to interact is actually being changed by Artificial Intelligence. The main thing that this course teaches is the main concepts in machine learning using applied examples in real life.

With this Apply Creative Machine Learning training candidates will come to know how exactly machine learning works, and how simple classification systems are built. This system can help make a discrimination between the information types, and the regression systems that are used for mapping interactions to different outputs. The candidates will be understanding the full capacity of the abilities of Machine Learning keeping in mind its relationship with creative industries.

The Introduction to Trading, Machine Learning & GCP online course is an intermediate level of course. Students can look up the programme on the official website of Coursera. In this programme, students will learn about trading, its features, trends, and aspects related to trading. The course will discuss the different quantitative strategies that are considered for trading and trading structure. 

The course also talks about Google cloud and machine learning aspects in the programme. The Introduction to Trading, Machine Learning & GCP certification syllabus of the program is categorized on a weekly basis and demands four weeks for the program. 

Students are free to set their schedules according to their willingness and the entire program can be completed in 5 hours. Through the assignments and exercises, the students are able to understand every concept properly. At the end of the Introduction to Trading, Machine Learning & GCP certification course, students can also complete the procedure of getting a certificate if they want to be a certified user of the program.

The online program on Advanced Machine Learning and Signal Processing by Coursera is a part of the series of programs that are offered in the domain of “advanced machine learning and signal processing”. The Advanced Machine Learning and Signal Processing training is part of the courses that are offered by IBM on advanced data science specialization. In the course, the frameworks for python using SparkML and Scikit-Learn will be introduced. The Advanced Machine Learning and Signal Processing certification syllabus will be covered on the digital platform within a time frame of 28 hours.

Machine Learning is a highly demanded skill in the 21st Century. ML is the application of Artificial Intelligence  that provides systems with the ability to learn and improve from experience, without any explicit programming and human intervention. It is the study of computer algorithms that automatically improve through experience. ML has now become an integral part of our lives, and data science and AI professionals are looking to upskill in this. In Coursera’s Machine Learning training course, you will learn the most effective ML techniques and gain experience in their practical applications with precision. 

The Coursera Machine Learning programme teaches the extensive theories behind Machine Learning so that you can quickly learn to apply the techniques to new problems. Besides Machine learning, this course also provides an introduction to data-mining, artificial neural networks, logistic regression, and statistical pattern recognition. 

This Machine Learning certification course is offered by Stanford University and is taught by one of the top educators of Stanford. It takes approximately 60 hours to complete this course. It has 18 modules rife with pre-recorded online lectures, readings and practice exercises for self-evaluation.