Programme Objectives
insAnalytics’ academic wing aims to equip participants with cutting-edge skills in the most rapidly growing field in today’s Analytics landscape viz. Data Science (Machine Learning, Big Data Analytics), IoT, Artificial Intelligence, Image Processing and their application in the industry. Our faculty members bring a unique blend of decades of Data Analytics industry experience and relevant academic background.
Our programs offer strong conceptual learning, complemented with business case-studies, use-cases, assignments, real life examples and projects.
Who Should Go For The Program
Our programs have been designed & developed primarily for professionals who wish to add the high-demand Data Science & Data Analytics skillset to their bouquet of skills.
The insAnalytics Training Edge - Our Differentiators
- DDesigned to balance learning with application
- IIndustry-oriented case-studies
- FFaculty are industry experts
- FFlexibility to pick-and-choose any delivery platform
- EExtend your learning to any course module of choice
- RReal-life business Problems as hands-on exercises
FOR EARLY BIRD DISCOUNT
Request A CallbackCURRICULUM HIGHLIGHTS
- Learn nuances unique to Big Data when solving business problems.
- Case study-based approach to look at real world problems.
- Learn the art of using Data Visualization to drive & support decision-making for senior management in your organization.
- Designed for multi-industry requirements – retail, banking, telecom, manufacturing etc.
- Build analytics-driven interactive business dashboards.
- Learn Artificial Intelligence and Machine Learning, Natural Language Processing, RPA lifecycle.
- Hands on using UiPath.
- Essential of Raspberry pi, sensors and Python.
- Collection of data over internet for further analytical processing.
- Quantify, analyze and improve marketing performance.
- End-to-end marketing analytics from market research till ROM.
- Learn state-of-art HR management through Machine Learning techniques.
- Learn how to leverage these techniques for Balanced Score Card, KPI identification etc.
- Case studies in Workforce Analytics, Employee Attrition, Talent Management.
- Understand major algorithms used for Machine Learning.
- Solve business problems using Machin Learning techniques.
- Learn nuances of Data Management while implementing Machine Learning Algorithm.
- Case study-based approach to look at real world problems.
- Forecast business parameters using advanced quantitative techniques.
- Time series forecasting and other predictive analysis.
- Address business challenges using business forecasting.
- Learn the difference between Machine Learning and Deep Learning, and the requisite fundamentals for Deep Learning.
- Learn algorithms for image manipulation, characterisation, segmentation.
- Learn to operate TensorFlow to manage neural networks and interpret the result
- Access past performance and predict future financial scenarios.
- Case study-based approach to look at real world problems.
- Master and apply the core methodologies used in supply chain analysis and modelling including statistics, regression, optimization and probability.
- Learn the role/ application of Descriptive Analytics, Predictive Analytics in Supply Chain.
MEET OUR INDUSTRY EXPERTS
Goutam Das
M. Tech. (Computer Engineering), IIT Kharagpur
Dr Nidhan "Neal" Choudhuri
Ph.D. (Statistics), Michigan State University
Dr Mousumi Duttaray
PhD (International Economics), Indiana University Bloomington, USA
Somnath Sinha
B.Tech (Electrical Engineering), IIT Bombay (Powai)
Prof. (Dr.) B. B. Chakrabarti
Ph.D in Economics, Gold Medallist PGDM, IIM Calcutta; Gold Medallist - BE, Jadavpur Univ. Fellow Member of the Institute of Cost Accountants of India (ICAI)
INDIVIDUAL SPEAK
