This course is specially designed keeping non-quantitative background people in mind. It will teach you the ins and outs of using Machine Learning for processing and deciphering Big Data, it will also show you how to design algorithms for your business. This course will teach you how to code using no-code tools and does not require any pre-requisite programming skills.
Who should Attend:
- Mid & Early Career professionals (Corporations/ Govt) working in IT, Manufacturing, supply chain.
- Startup, business owners and entrepreneurs
- Looking forward start career in AI and data science.
Syllabus - What you will learn from this course.
Module 1 – Big Data and Artificial Intelligence
You will become familiar with Big Data and investigate the application of machine learning across a variety of business domains while working through this topic. You will also get an understanding of the processes of data analysis and extraction, as well as the ways in which digital technologies have been employed to grow and transform enterprises. You will also receive an in-depth examination of data management tools, as well as the best way to put them into practise and the significance of data warehouses. At the conclusion of this lesson, you will have a better understanding of how machine learning may be applied as a multipurpose technology, as well as some of the most effective strategies, procedures, and guidelines for data mining.
4 Lectures, 1 quiz.
Module 2 Training and Evaluating Machine Learning Algorithms
Logistic regression and neural networks are only two of the Machine Learning techniques that will be compared in great detail throughout this subject. You will also gain an understanding of Deep Learning, as well as its connection to neural networks, as well as the most effective methods for optimising Machine Learning algorithms. In last, you will become familiar with loss functions and learn the most effective ways to measure and review errors so that the integrity of your algorithms may be preserved. You will have gained knowledge of the methods of machine learning by the time that this module ends. You will also have gained knowledge of the advantages and disadvantages of deep learning, as well as the most effective ways to improve the algorithms' precision and accuracy, as well as the data that should be used to train those algorithms.
8 Lectures, 1 quiz.
Module 3 – ML Application and Emerging Methods
The focus of this unit is on the use of Machine Learning to NLP and the development of novel data through generative modelling. You will also be focusing on AutoML and learning how to make the most of automated procedures to increase the effectiveness of your algorithms. The no-code Machine Learning tool Teachable Machine, which was designed to make Deep Learning and Machine Learning more accessible, will also be covered in this course. You will have the ability to use AutoML in your algorithms by the time this module is finished, and you will also have the ability to explore and use Teachable Machine in practise for no-code solutions to developing algorithms.
6 Lectures, 1 quiz.
Module 4 - Industry Interview
In this lesson, you will hear from an industry expert who will provide you with insightful information regarding data sampling and the construction of realistic and useable models. You will have the opportunity to study real-world solutions and learn how one of the most successful global businesses handles data difficulties. At the end of this module, you will have had the opportunity to hear from a leading industry expert in their field and will have gained first-hand knowledge and an understanding of how Big Data plays a role in maintaining privacy in data as well as utilising that data to enhance your marketing, content, and refine your algorithms. This will take place at the conclusion of this module.
2 Lectures, 1 quiz.
About Program Directors:
Prof. Shivshanker graduated from IISc Banaglore with PhD in Management Science and has master’s degree and bachelor’s Degree from IIT Roorkee and NIT Raipur in mechanical engineering. He has worked in past with Mphasis-Nextlabs in the domain of data science and as R&D Engineer with Mahindra & Mahindra Automotive. His research interests lie in data science, machine learning and game theory, teaches similar courses at IIM Visakhapatnam and published research in the same domain.
Prof. Prashant Premkumar Nayar Ph.D. (Quantitative Methods and Operations Management), IIM Kozhikode
Prof. Prashant Premkumar Nair holds a PhD degree from IIM Kozhikode. Prior to joining IIM Visakhapatnam, he worked as Assistant Professor at IRMA. He has earlier worked with Vedanta, Torrent Power, Deloitte, and NIRMA University in various capacities. His research interests lie in the areas of Network Optimization Problems and Data Analytics.
|Women||₹65,000 + 18% GST|
|Women Foreign Participants||$1000|
|Others||₹80,000 + 18% GST|
|Other Foreign Participants||$1500|
(Exclusive: Encouraging women in data science)
Fees for women candidates: INR 65,000 + 18% GST
All others: INR 80,000 + 18% GST
Accommodation and food by IIMV
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Contact us: firstname.lastname@example.org | +91 75693 09207