|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|
|Machine Learning with Python Offered by IBM||Machine Learning||Online self study|
|Post Graduate Program in Data Science and Machine Learning||Data Science||Blended Classroom|
|Big Data and Machine Learning Prodegree||Big Data||Noida , Delhi , Gurgaon , Chandigarh , Bangalore , Hyderabad , Chennai , Ernakulam||Online Classroom|
|Marketing Applications of Machine Learning and Artificial Intelligence||Machine Learning||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|
|The Top 5 Machine Learning Libraries in Python||Machine Learning||Online self study|
|Become a Machine Learning Engineer||Machine Learning||Online self study|
|Machine Learning||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|
|Machine Learning A-Z™||Data Science||Online self study|
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.
This course dives into the basics of machine learning using an approachable, and well-known programming language, Python. In this course, we will be reviewing two main components: | First, you will be learning about the purpose of Machine Learning and where it applies to the real world. | Second, you will get a general overview of Machine Learning topics such as supervised vs unsupervised learning, model evaluation, and Machine Learning algorithms.
Designed to give students a comprehensive analytics education with a combination of online and in-person sessions, projects and seminars by industry leaders and hands-on learning in the Jigsaw Lab, PGPDM has already made a significant impact, being ranked #2 in the ‘Top 10 Executive Data Sciences Courses in India’ by Analytics India Magazine for 2017 & 2018. | Comprehensive data science and machine learning education
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.
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.
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
A machine learning engineer is a person who builds predictive models, scores them and then puts them into production so that others in the company can consume or use their model. They are usually skilled programmers that have a solid background in data mining or other data related professions and they have learned predictive modeling. In this course, we are going to take a look at what machine learning engineers do. We are going to learn about the process of building supervised predictive models and build several using the most widely used programming language for machine learning: Python. There are literally hundreds of libraries we can import into Python that are machine learning related. A library is simply a group of code that lives outside the core language. We “import it” into our work space when we need to use its functionality. We can mix and match these libraries like Lego blocks.
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 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.
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 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.