Executive Development Programme in Data Science Using Python, R and Excel

XLRI - Xavier School of Management

Operations, Production and Decision Sciences

About Programme

Today every business is trying to engage with data science in one form or another. Unfortunately, very few businesses have been able to even grasp the idea of what constitutes data science, let alone a useful or profitable implementation of the same. The phrase - data science triggers thoughts on related terms like business analytics, operations research, business intelligence, competitive intelligence, data analysis and modeling, etc. In addition, the latest craze doing the rounds is big data analytics. No wonder an average business manager is utterly confused about how to start introducing data science in the organization. Meanwhile, popular press keeps exhorting managers not to be late in embracing data science. The consequence is that business managers employ technical solutions without having a good idea of how data science can actually add value to their businesses. To preside over a successful implementation of data science in the organization the managers must have a good understanding of the basics, and it is quite impossible to get a feel of data science without getting one’s hands dirty. This course is an entirely hands-on approach to data science where participants would be working with data sets to generate insights for businesses. The tools that we will use are Python, R and Excel. The objective of this course is to introduce participants to the world of data science and who have not got a foothold into the techniques. The purpose of this course is to strip away all the distractions around data science – codes, tools, etc., and teach the techniques using practical cases that can be understood and appreciated by someone with an elementary knowledge of mathematics.

Programme Content

1. Introduction to R and Python

• Installing R, Python, Jupyter Notebook and R Studio

• Basic Data Structures in Python and R

• Writing Functions

• Use of Loops

• Basic Differences Between R and Python

2. Advanced Features in Excel

• Important Functions in Excel

• Optimization Using Solver

3. Sources of Data

• Important Data Sources

• Scrapping Data from Websites

4. Data Wrangling in R and Python

• Managing Missing Data

• Managing Outliers

• Removing Duplicate Rows

• Making Data Tidy

5. Introduction to SQL

• Introduction to SQL

• Accessing Data in R/Python using SQL Queries

6. Data Visualization

• Visualizing Data

7. Linear Algebra and Calculus

• Vectors, Matrices, and Tensors

• Differentiation

• Understanding Gradient Descent Algorithm

8. Statistics

• Types of Data

• Exploratory Data Analysis

• Sampling Distributions

• Type I and Type II Errors

9. Text Analysis

• Cleaning Text

• Text Representation

• Sentiment Analysis

10. Time Series Analysis

• Time Series Forecasting

• Forecasting using Prophet

11. Machine Learning

• Understanding the Maths of Machine Learning

• Building Machine Learning Models (Regression and Classification)

• Hyperparameter Tuning

• AutoML

12. Deep Learning

• Understanding the Maths of Deep Learning

• Building a Deep Learning Model to Predict Stock Prices

• AutoML in Deep Learning

13. Case Studies in Data Science

• Building Models in Different Functional Areas of Management

Pedagogy

The primary method of instruction will be through LIVE lectures that will be beamed online via Internet to student desktops/laptops or classrooms. The pedagogy will comprise lectures, case walkthroughs, and analytical exercises imparted by XLRIs faculty. Concepts will be explained using examples drawn from the real life. All enrolled students will also be provided access to the Cloud Campus through which students may access other learning aids, reference materials and assessments, case studies, projects and assignments as appropriate. Throughout the duration of the course, students will have the flexibility to reach out to the professors, real time during the class or offline via the Cloud Campus to raise questions and clear their doubts.

Programme Audience

Professionals who want to learn practical aspects of data handling across applicable areas like Big Data, IT Services, Marketing, eCommerce, Research etc. Project Managers, Business Managers and Senior Leaders who have the responsibility to manage large data analytics/big data based projects and would like to gain an understanding of this domain. Young professionals and managers who have little or no formal education in Business Analytics, but who now feel the need to embrace technologies which will help them generate insights from data. Executives with analytical aptitude who are interested in and want to learn Data Analytics through hands on practice on popular tools. This programme is entirely hands-on and so it is recommended, though not a necessity that students have two devices – one to follow the lecture, and the other for hands-on practice on Excel and R. However, it is mandatory that the sole or primary device must be a laptop or desktop to facilitate hands on practice on tools.

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Prashansa Uttam

Programme Advisor

+91 9403890085[email protected]Mon – Fri, 9am – 5pm IST

XLRI - Xavier School of Management

Executive Education Office

https://www.xlri.ac.in

Jamshedpur, India

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