|Course or Certification Name||Category||Location||Mode of learning|
|Machine Learning Engineer||Machine Learning||Online self study|
|Machine Learning Advance certification Training||Machine Learning||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Post Graduate Program in Data Science and Machine Learning||Data Science||Classroom|
|Big Data and Machine Learning Prodegree||Big Data||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Applied Machine Learning With R||Machine Learning||Online self study|
|Machine Learning In The Cloud With Azure Machine Learning||Machine Learning||Online self study|
|Machine Learning With TensorFlow The Practical Guide||Machine Learning||Online self study|
|Google Cloud Platform Big Data and Machine Learning Fundamentals||Machine Learning||Online self study|
|Advanced Machine Learning with Deep Learning||Machine Learning||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Marketing Applications of Machine Learning and Artificial Intelligence: What can ML and AI do for your organization?||Classroom|
|Machine Learning||Online self study|
|Become a Machine Learning Engineer||Online self study|
|Machine Learning A-Z™||Data Science||Online self study|
|PG Diploma in Machine Learning and AI||Machine Learning||Online self study|
|Machine Learning with Python Training||Machine Learning||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
As more and more companies are looking to build machine learning products, there is a growing demand for engineers who are able to deploy machine learning models to global audiences. In this program, you’ll learn how to create an end-to-end machine learning product. You’ll deploy machine learning models to a production environment, such as a web application, and evaluate and update that model according to performance metrics. This program is designed to give you the advanced skills you need to become a machine learning engineer.
This course is an advanced level training on Machine Learning application and algorithms. It will ensure you get hands on experience in multiple and highly used machine learning skills in both supervised and unsupervised learning. This machine learning training ensures you can apply machine learning algorithms like Regression, clustering, classification and recommendation.The unique case study approach ensures you are working hands on with data while you learn. Finally the course trains you in deep learning and Spark Machine learning, skills which are in great demand today.
The University of Chicago Graham School and Jigsaw Academy, India’s top online school for analytics, together provide students with the superior training necessary to draw insights from real data and to apply analytical skills to solve real problems with the launch of the Integrated Program in Data Science and Machine Learning (IDM). IDM is highly applied in nature, integrating business strategy, project-based learning, simulations, case studies, and specific electives addressing the analytical needs of various industry sectors. | This program is a blend of in-person and online classes that will include hands-on learning in the Jigsaw Lab and projects & seminars by industry leaders. All the in-person sessions will be held in Bangalore, India. The content and curriculum for the course have been jointly designed by lecturers from UChicago and industry experts from Jigsaw Academy.
The Big Data and Machine Learning Prodegree, in association with IBM as the EdTech Partner, is a first-of-its-kind 160-hour certification course providing in-depth exposure to Data Science, Big Data, Machine Learning and Deep Learning. The rigorous industry-aligned curriculum offers a comprehensive understanding of Python, Spark and Hadoop for careers in Machine Learning and Big Data. The program also features seven industry projects and periodic interaction with industry leaders in the Machine Learning Ecosystem.
Applied Machine Learning with R is a hands-on course Machine Learning and Artificial Intelligence course. This course covers the core concepts of machine learning, along with machine learning algorithms. You will also learn how to implement those machine learning algorithms with R and after completion of the course, you will be able to use them in your own projects.
In this course, we will discuss Azure Machine Learning in detail. You will learn what features it provides and how it is used. We will explore how to process some real-world datasets and find some patterns in that dataset.This course teaches you how to design, deploy, configure and manage your machine learning models with Azure Machine Learning. The course will start with an introduction to the Azure ML toolset and features provided by it and then dive deeper into building some machine learning models based on some real-world problems
This course gives an insight into the basics of Tensorflow covering topics like tensors, operators and variables. It is a good option to master machine learning, its types and various main algorithms including linear regression. Furthermore, this course also covers advanced machine learning like a neural network, convolution neural network and others. Here, you’ll also gain the practice by implementing it in a project on Deep Neural Network. | Machine Learning With TensorFlow is a professional programme. It provides a complete insight of Tensorflow, tensors, operators and variables. Machine Learning With TensorFlow also includes other topics like – Getting started with Tensorflow, Tensorflow Basics, Machine Learning Basics, Main Algorithms including linear regression, Advanced Machine Learning
This 1-week accelerated on-demand course introduces participants to the Big Data and Machine Learning capabilities of Google Cloud Platform (GCP). It provides a quick overview of the Google Cloud Platform and a deeper dive of the data processing capabilities.
Machines have been driving our existence since the first industrial revolution to the current industry 4.0. It is, thus, imperative to be a part of this revolution by acquainting yourself with the formidable technology platforms like Machine Learning, AI, & Deep Learning | In this age of innovation and disruption, the technology landscape changes rapidly. One has to be on their toes all the time to remain updated and upgraded. In such a scenario, a course that incorporates the concepts of Advanced Machine Learning with Deep Learning in one package can be the best bet to learn and train yourself | Cognixia offers a comprehensive training package based on a case-study approach where participants are exposed to the pragmatic aspects of learning Advanced Machine Learning, AI, & Deep Learning
This management development programme will introduce you to some of the key concepts behind machine learning and artificial intelligence, including the differences between Strong and weak AI. This MDP will explain the different approaches to AI, including machine learning, and the practical applications for new AI-enhanced technologies. With the help of business frameworks, understand how these prediction machines can be built in your business context.
This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: | (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). | (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). | (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI). | The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas.
Learn advanced machine learning techniques and algorithms and how to package and deploy your models to a production environment. Gain practical experience using Amazon SageMaker to deploy trained models to a web application and evaluate the performance of your models. A/B test models and learn how to update the models as you gather more data, an important skill in industry. | This program is intended for students who already have knowledge of machine learning algorithms.
This course has been designed by two professional Data Scientists so that we can share our knowledge and help you learn complex theory, algorithms and coding libraries in a simple way. | We will walk you step-by-step into the World of Machine Learning. With every tutorial you will develop new skills and improve your understanding of this challenging yet lucrative sub-field of Data Science.
Machine Learning with Python course discusses concepts of the Python language such as file operations, sequences, object-oriented concepts, etc. along with some of the most commonly leveraged Python libraries like Numpy, Pandas, Matplotlib, etc. The course will then move on to introduce learners to the detailed mechanisms of Machine Learning. Learners will understand in detail the significance of the implementation of Machine Learning in the Python programming language, and leverage this knowledge in their role as data scientists. | After completing the course, one would have learnt about tools to train machines based on real-world situations using Machine Learning algorithms, as well as to create complex algorithms based on concepts related to deep learning and neural networks. During the latter stage of the course, learners will be introduced to real-world use cases of Machine Learning with Python for a holistic learning experience which would prepare them to create applications efficiently.