IIT Roorkee Post Graduate Certificate Programme in Decision Making Using Data Science

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About Course

IIT Roorkee’s Post Graduate Certificate Programme in Decision Making Using Data Science (PGCP DMDS) is designed to enhance participants’ perception, concepts, and hands-on skills in data science for making decisions that can produce business value. Participants will learn the fundamentals and core analytics in data science, learn how to prescribe or suggest the best course of action in various real-world applications, and develop proficiency in the technologies that help to implement data science solutions.

What Will You Learn?

  • Gain deeper understanding of concepts in data science.
  • Hands-on experience with big data management and analytics.
  • Hands-on experience with several technologies including Python, SQL, Tableau, etc.
  • Know and understand applications of data science in different domains.
  • Hands-on experience with various datasets and analytics.
  • Become empowered for value-oriented decision-making using data science.

Course Content

Module 1: Foundation for Data Science
In this module, you will learn about the foundations of Data Science and its latest inventions like GenAI. It is important that you are aware about the tools and technologies that are used for handling data.

  • Emerging technologies and AI
  • Understanding data science and AI
  • Overview of Generative AI (GenAI)

Module 2: Technical Foundation for Data Science
This module will cover topics on data structures in Python including lists, tuples etc., loops, control structures, functions, NumPy, Pandas, MatplotLib. This module will help gain understanding of the Python programming language.

Module 3: Exploratory Analytics
Exploring the data and understanding that it is a really important step even before we apply any Machine Learning models. Visualising the data helps to share the insight with all the stakeholders and helps in getting greater insights. You will be using Tableau for visualising the data.

Module 4: Machine Learning
This module will introduce basics of machine learning modules for supervised and unsupervised learning.

Module 5: Introduction to Hadoop and Big Data
This module will introduce basics of Hadoop and Big Data

Module 6: Inferential and Causal Analytics
Making inferences is a core topic in data science. It includes making hypothesis about variables or relationships in a larger population and conducting assessment of the hypothesis based on sample (data) from the population. Causal inferences about relationships examine whether X causes Y and is basically a step bit further than just knowing that X and Y are correlated. Inferences using both experimental and observational data will be discussed.

Module 7: Big Data Analytics
Recent years have seen the rise in the volume of data. As a data scientist, it is essential to know the basic concepts and tools involved in management of big data and computation using big data. You will also learn supervised and unsupervised analytics using three different types of data – time series, networks, text.

Module 8: Prescriptive Analytics
How to make decisions about what to do next? Combine results from machine with human judgement to make optimal decisions. You will study different cases of decision-making including demand forecasting, investment choices, making recommendations, detecting frauds, lead conversion, and others.

Module 9: Decision Support Systems
In the age of big data, it is an added advantage to have knowledge about the hardware and architecture on which data science is eventually deployed. We will also discuss how such systems overlap with emerging Industry 4.0 technologies like blockchain and IoT.

Module 10: Data-driven Decisions for Strategic Business Value
Do all decisions based on analytics provide business value? Combine analytics and systems thinking to innovate transformative solutions. Several case studies from recent start-ups will be discussed.

Capstone Project
Build an end-to-end data science project on your own. Work on a topic that interests you to collect required data, process and analyse it, deploy model on the web, and report your results. You can also select a topic from a pre-defined list.

Hackathons
By participating in a hackathon, you'll sharpen your problem-solving skills, enhance your teamwork abilities, and gain practical experience in developing innovative solutions to real-world challenges.

Tools