Machine Learning Certificate Courses

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.

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.

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. 

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.

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.

Also Read: 

• Career as a Computer Programmer
• Essentials of Data Science with R Software-2 Sampling Theory and Linear Regression Analysis

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 9 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.

The Unsupervised Learning online course by Udacity aims to educate you on Unsupervised Learning concepts. During the course, you will study and practice a wide range of Unsupervised Learning approaches. These include clustering, information theory, randomised optimisation, transformation and feature selection, etc.

The Unsupervised Learning online programme focuses on how you can utilise Unsupervised Learning methods to discover structure in unlabelled data. You will also learn how to use it for identifying patterns and analyse data. The course provides detailed insights into the best practices and important techniques for Machine Learning.

The programme duration is approximately one month. The Georgia Institute of Technology, USA offers Udacity’s Unsupervised Learning online training. This intermediate-level programme includes rich video content delivered by expert instructors. Moreover, you will learn via interactive quizzes and reading resources. You will also work on a final project to gain practical knowledge of ML.

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 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. 

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.

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. 

The Machine Learning for Data Analysis certification course is a 10 hours 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.

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. 

Introduction to Machine Learning in Sports Analytics is an intermediate-level online course provided by Coursera which is one of the leading online course providers.  The online certification programme will guide the learners on how to use machine learning in sports analytics. Offered by Coursera, Introduction to Machine Learning in Sports Analytics Certification Course is the last course in the Sports Performance Analytics Specialization offered by the University of Michigan. 

Introduction to Machine Learning in Sports Analytics Certification Syllabus will discuss the machine learning techniques, the prediction of athletic outcomes with machine learning, and many more. Introduction to Machine Learning in Sports Analytics Certification by Coursera can be taken by learners who have familiarity with Python.