Online Machine Learning Courses & Certifications

The Deep Learning course (with Keras and Tensorflow) certification training course, will educate participants on deep learning concepts and models using Keras and TensorFlow frameworks, to carry out deep learning algorithms. The Deep Learning course (with Keras and Tensorflow) certification training online provides 34 hours of blended learning, industry projects, and dedicated project mentoring sessions from industry experts that will help you prepare for a career as a Deep Learning engineer.

The Deep Learning course (with Keras and Tensorflow) certification training offers you a competitive edge in solving applications without human intervention. The training provides you with ways of expanding the limits of what a computer system can accurately inspect. The Deep Learning course (with Keras and Tensorflow) certification training online will help you differentiate between Deep Learning, Machine Learning, and Artificial Intelligence.

Deep Learning course (with Keras and Tensorflow) certification training by Simplilearn benefits IT developers and testers, data analysts, junior data scientists, analytics professionals, software engineers, statisticians, students, and professionals indulging in data across every field. The Deep Learning course (with Keras and Tensorflow) certification training online will help the candidates in creating deep learning models to interpret the results in building a deep learning project. 

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.

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.

Machine learning algorithms are a subset of artificial intelligence (AI) that has been developed to match human intelligence. However, machines supersede the human brain at analysing data and gaining insights about businesses, and machine learning algorithms. They have found relevance in various industries and different functional areas, which makes it a hot topic for study and thus this course-Machine Learning with Business Applications by IIM Bangalore.

Machine learning algorithms can be divided into four sectors- unsupervised learning algorithms, supervised learning algorithms, evolutionary learning algorithms and reinforcement learning algorithms. In Machine Learning with Business Applications Certification Syllabus, candidates will be exposed to different machine learning algorithms and their applications through interactive case studies from various industries.

The ‘Online Machine Learning Program - Self-Paced’ is provided by the education platform ‘Eduplusnow’ and the course is certified by the Indian Statistical Institute in Pune. The machine learning training program also helps the students to understand the methods involved in the software tools such as Python. 

The students gain practical experience by applying the concepts of machine learning in the projects and assignments that are a part of the course curriculum. The course study is about the machine learning algorithms used along with Python and the scope of the machine learning principles in the real world to counter challenges in technologies. 

The learners in this ‘Online Machine Learning Program - Self-Paced’ training will be able to build their business and career with the knowledge and certification gained. The course is guided by the professional faculty who provide valuable insights to become experts in machine learning.

Machine Learning - Linear Regression certification course is developed by Leaps Analyttica TreasureHunt and is delivered by FutureSkills Prime, which is aimed at participants who are looking for a comprehensive training program to learn the functionalities of linear regression in a variety of machine learning and data science activities, as well as being used by organizations for future projections. Machine Learning - Linear Regression online course provides the expertise to design and validate a viable linear regression model on legitimate datasets.

Machine Learning - Linear Regression online classes by FutureSkills Prime will take the participants through the fundamental concepts of machine learning and linear regression including both simple and multiple linear regressions. This course also covers topics like exploratory data analysis, model iterations, variable selection, variable transformations, overfitting, and R square. By the end of this training, participants will be able to pre-process data and evaluate linear models as well as acquire an understanding of various stages of predictive modeling.

Machine Learning for Computer Vision training Certification course Machine Learning in Computer Vision Certification Programme instils a feeling of curiosity and hunger for knowledge related to the fascinating avenue of machine learning in computer-enabled vision. The current domain holds great scope for individuals possessing a budding interest in it and proves to be a coupled breakthrough in providing optimum academic learning. The course will fall as the ideal training course for startup founders, engineers and computer scientists.

The curriculum targets various application domains for the resolution of industrially significant real-life problems while concentrating on its algorithm from the human biological vision. The Machine Learning for Computer Vision training course deals with a plethora of problems and offers practicable solutions to the same by emphasising computer vision.

The faculty from IIT and various other eminent institutes discuss at length various methods of processing, acquiring, analysing, and understanding the extraction of data from the real world and digital images to produce information. Learners will find themselves acquiring appreciable knowledge of diverse sub-domains as well which are related to object recognition, motion estimation, and video tracking which candidates will be able to implement in navigation, medicine, and object modelling, amongst other things.

The course provided by Edureka in Machine Learning with Mahout Certification Training will help the participants lay a strong foundation for themselves in the study of fundamental machine learning techniques which consists of a broad range of algorithms of k-means clustering, Support Vector Machines, Mahout on Amazon EMR and Hadoop, Collaborative filtering to recommendation system as well as Random Forests. 

Since in the current digital market there has been an exponential increase in the amount of data available, the markets are in demand of professionals who can turn vast amounts of data into reliable and useful information, without taking a lot of time. 

This course will help the candidates master skills that are demandable in the market of today by providing training through various efficient study materials. Expert guidelines will also be granted to the students for clarifying queries as soon as they arise. This course covers basic education about Java and Hadoop, so even freshers are welcome to apply.

The Machine Learning Zero to Hero certification course offered by the Indian Institute of Technology Kanpur is a six-week online certification course. The training is structured to introduce machine learning's fundamental concepts and popular algorithms. Candidates will learn through a problem-solving approach by practising exercises in Python.

The Machine Learning Zero to Hero online course teaches about the up to date and supervised learning algorithms, decision tree, linear regression, k-nearest neighbour, and logistic regression concepts. The curriculum also highlights Bayesian learning, support vector machines, and kernels and neural networks accompanied by the introduction of Deep Learning. Candidates will learn about basic clustering algorithms and feature reduction methods.

The computational learning theory basics are discussed in the Machine Learning Zero to Hero training. Furthermore, the online course curriculum consists of complex topics such as variance and bias, overfitting, hypothesis space, cross-validation, and evaluation strategies. What's more, you can earn a certificate of completion at the end of the programme to showcase your skills in machine learning.

The Introduction to Machine Learning certification course includes understanding, analysis, and challenges of various Machine Learning approaches. This programme has a comprehensive learning curriculum. With assignments and evaluation tests, candidates need to qualify in a final MCQ quiz to receive the certificate.

The Introduction to Machine Learning certification syllabus is divided into four sections. Each of these individually focuses on different learnings and models of ML. These include supervised and unsupervised learning, ensemble, and non-linear methods. In particular, topics discussed include basic clustering algorithms, supervised learning algorithms, decision trees, support vector machines, and k-nearest neighbours.

Learners can access the learning materials only for the duration of the course. Anyone associated with this specialised field of computer science and Information technology can take up the Introduction to Machine Learning training.  Since this is a paid programme, students can only begin learning after paying the necessary fee. Alternatively, a demo version of the course is available.

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.

A part of the multiple series programme, the online session on Supervised Machine Learning: Classification by Coursera provides the students with a detailed emphasis on the main types of modelling that are involved with the genre of machine learning. The students will learn elaborately to train the predictive models that are involved and used across various domains. The Supervised Machine Learning: Classification certification syllabus will be covered on the online platform by the students over a time frame of 11 hours. The course will train the students professionally in the domain of machine learning.

Codecademy’s Build a Machine Learning Model with Python certification course will teach you about building machine learning models with Python. You’ll learn how such models help find patterns in data for decision-making, and thus, be fluent in why machine learning is vital today. The curriculum also offers step-by-step guidance, where you’ll know exactly where to begin and what topic to learn next. 

The Build a Machine Learning Model with Python certification syllabus is built to make you skilled in machine learning. As such, it covers all the vital concepts, completing which you’ll be able to scrub for inaccurate data points using Python. You’ll further be able to reformat that data to make it more useful. The course’s topics will also help you understand when to use predictive techniques like classifications or regressions and exploratory techniques such as clustering. 

The Codecademy Pro feature will give you access to additional learning content, including Python 3, Jupyter Notebooks, pandas, etc. It will also award you the GBuild a Machine Learning Model with Python certificate, but you’ll have to buy the Pro subscription.

The Crash Course in Prolog Programming (M) by  E&ICT Academy, IIT Kanpur, will be organized for six weeks. The course will be highly beneficial to the students as well as professionals and teachers. The Crash Course in Prolog Programming (M) certification benefits them by providing a comprehensive course on “Prolog programming.” The real-world applications and the techniques related to “Prolog Programming” will be covered in the session. Lectures will be delivered in both Hindi and English languages. The important chapters such as Installation, Rules, Facts, Complex terms/structures, Variables, Comparison, If Statement, Looping, and others will be covered in this crash course.

20+ End-To-End Machine Learning Projects & Deployment online course aims to teach beginners and intermediate data science enthusiasts the most efficient ways to deploy machine learning models while practicing on projects to gain a better understanding of the course. The course is designed for the participants who want to master machine learning with python programming and utilize it for data analysis operations and become professional data scientists. This course will show them how to deploy their machine learning models in the cloud the way the industry does it.

20+ End-To-End Machine Learning Projects & Deploymentonline certification is created by Mr. Britt - Data Scientist, Product Manager & Instructor and is made available through Eduonix, an educational organization that provides learning materials for skill development to individuals who want to advance in their careers. Participants who wish to enroll in the 20+ End-To-End Machine Learning Projects & Deployment online training are advised to have a basic knowledge of Python Programming and machine learning to make their learning more efficient and effective. 

Practical Machine Learning, available on Coursera, is administered by  Johns Hopkins University to expose the students to the realm of machine learning along with a thorough practical training with the help of numerous practical applications.  Practical Machine Learning Certification Syllabus developed by industry experts and experienced professors will walk the students through concepts of sets, overfitting, regression, classification trees, Naive Bayes, random forests, and error rates. 

Practical Machine Learning Certification Course, provided by Coursera, will shed light on numerous topics related to machine learning including algorithms, evaluation, data collection, and feature creation. Practical Machine Learning Certification by Coursera prepared by Jeff Leek, Ph.D., Roger D. Peng, Ph.D., and Brian Caffo, Ph.D. with an emphasis on facilitating the learners to practice the application of machine learning. 

Machine Learning: Regression is a certification programme offered completely in the online mode. In the course by the University of Washington, the students will be exposed to machine learning, particularly regression. Machine Learning: Regression Certification Syllabus will talk about regression which is predictive modelling in machine learning that will help to foresee the outcomes analyzing the algorithm. 

In the Machine Learning: Regression Certification Course, offered by Coursera, the candidates will learn the regression based on the case study of the ‘Predicting Housing Prices’ where the students will come up with a model that will predict a continuous value/price based on the input features such as a number of bathrooms, bedrooms, etc. Machine Learning: Regression Certification by Coursera is the second in the four courses of Machine Learning Specialization. 

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. 

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 & Deep Learning in Python & R certification course was created by Start-Tech Academy and is available on Udemy for candidates searching for a comprehensive machine learning and deep learning training program that will help them start a successful career in the fields of data science, deep learning, machine learning, Python, or R programming. The Machine Learning & Deep Learning in Python & R online course provides the methodologies for creating predictive models in R programming and Python to address business challenges and establish a business strategy.

Machine Learning & Deep Learning in Python & R online classes by Udemy contains 35 hours of HD video lectures as well as 4 articles covering subjects such as decision trees, KNN logistic regression, random forest, SVM, linear discriminant analysis, data collecting, and data preprocessing. This course also includes a portion that discusses all of the actions that should be taken when solving a business problem using a linear regression model.

Machine Learning & Deep Learning in 31.5hrs online certifications is developed by Mario Favaits - Certified AI Professional & Trainer and is offered by Udemy which is designed for those who want to learn the fundamentals of machine learning and deep learning to become certified data scientists. The Machine Learning & Deep Learning in 30hrs online course by Udemy takes a practical approach, using a logical sequence to help participants understand data science and machine learning principles effectively.

As no prior knowledge of coding is required, the Machine Learning & Deep Learning in 30hrs online classes begin with the fundamentals of linear algebra, calculus, and statistics. This course aims to give students a thorough understanding of topics such as artificial intelligence, machine learning, unsupervised learning, neural networks, computer vision, data augmentation, backpropagation, and random forest, as well as various data science tools such as Python, Pandas, Keras, and Colab.