IIM Kozhikode - IIM Kozhikode Certificate Programme in Data Science

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IIM Kozhikode Certificate Programme in Data Science
at
Emeritus
Overview

Boost your Data Science career by developing effective skills, functional expertise and strategic acumen

Duration	12 weeks
Total fee	₹71,750
Mode of learning	Online
Credential	Certificate

IIM Kozhikode Certificate Programme in Data Science
at
Emeritus
Highlights

Earn a certificate from IIM Kozhikode, ranked 15th in Asia Pacific in 2020
Enjoy Personalized Career Services with emeritus India Career Services
Three 90-minute workshops from career management industry experts
Learn through 32 Assignments and 7 Discussions, Peer Learning and Feedback
Job placement assistance from partner companies are published, applied to, and tracked to success via an online platform

IIM Kozhikode Certificate Programme in Data Science
at
Emeritus
Course details

Skills you will learn

Excel Data mining Data Modeling Python Data Science Business Analytics Hypothesis Testing Data analysis Predictive modeling Big Data

Who should do this course?

For business Leaders who look up to data science to drive organisational transformation across teams
For professionals looking to understand Data Science methodologies and implement them to achieve team/ organisation goals
For project Leaders who want to lead data-driven projects and teams within their organisation
For professionals who aspire to lead data-driven disruptions in businesses across various domains like Retail, Pharma, Healthcare, Material Sciences, etc

What are the course deliverables?

Outline the importance of data in making a business decision
Describe the people and processes involved in the data cycle
Learn how to use descriptive, predictive and prescriptive analytics to drive growth
Describe the spectrum of data analytics in business decisions
Use analytics to extract insights out of datasets and draw conclusions
Understand hierarchical clustering and get the big picture of large data sets

More about this course

This programme is designed for professionals from any domain looking to advance their careers
This course will provide you with skills that will give you an insight into modern data science practices

IIM Kozhikode Certificate Programme in Data Science
at
Emeritus
Curriculum

Data Analytic Thinking

Outline the importance of data in making business decision

Describe types of data and data categories

Describe the people and processes involved in data cycle

Compare the characteristics of small data and big data

Discuss the importance of data analytic for business decision making

Identify actions taken during the cross industry standard process of data mining

Discuss the data science links with other discipline

Data Analysis with Excel

Describe the benefits of using Microsoft Excel for making data-driven decisions

Calculate stastical averages using Microsoft Excel functions

Apply basic Microsoft Excel tools for data analysis

Perform different analysis on data using techniques like what-if analysis, goal seek

analysis, sensitivity analysis

Use filter function to remove duplicates and calculate subtotals

Data Analysis with Python

Review and delineate the evolution and purpose of Python

Describe and set up Python development environment

Practice coding with basic Python commands, operators and conditional statements

Explore and apply Python data structure concepts such as array, list, tuple, set and dictionary

Import python modules and packages

Import Python libraries such as NumPy, Pandas

Data Analytic Thinking

Describe the need of data preparation

Describe the sources of data

Evaluate and improve quality of data

Differentiate between hypothesis testing and exploratory data analysis

Explore categorical variables

Types of Data Analytics

Describe spectrum of business analytics

Describe application of descriptive analytics

Draw conclusions from a given set of data by using descriptive analytic techniques

Describe application of diagnostics analytics

Draw conclusions from a given set of data by using diagnostics analytic techniques

Describe application of predictive analytics

Draw conclusions from a given set of data by using predictive analytic techniques

Describe application of prescriptive analytics

Draw conclusions from a given set of data by using prescriptive analytic techniques

Data Modeling: Predictive Modeling

Discuss Cross Industry Standard Process in Data Modeling

Discuss a Generic data modeling process

Apply prior knowledge the address the business problems

Data Modeling: Fitting a Model

Discuss overfitting modeling

Explain data driven modeling

Describe decision tree and its types

Design a classification tree to resolve uncertainties

Data Clustering

Describe concepts of clustering and visualize data

Apply K-means algorithm to cluster the data

Apply Z-score method to standardize the data

Interpret the cluster center and create product segment

Use Dendrogram and Elbow Curve for estimating the number of clusters

Estimate the quality of clustering using Silhouette scores

Data Clustering: Hierarchical clustering

Explain the limitations of K-means clustering

Apply hierarchical clustering to the product segmentation and the Gaussian distributed dataset

Describe the DBSCAN clustering technique and its benefits

Apply K-Means, Hierarchical and DBSCAN clustering to the moon dataset

Discuss the limitations of clustering algorithms and techniques to address them

Association and Co-occurrences: Items That go Together

Discuss correlation and its characteristics

Perform association analysis by generating general association rules between market variables

Apply association rule to restrict frequently appearing data items

Apply association rule to identify frequency of conditional probability

Association and Co-occurrences: Measuring Suprises

List the measures of Suprise

Use Naïve method for measuring leverage

Use Apriorism algorithm for measuring leverage

Project Brief and Course Summary

IIM Kozhikode Certificate Programme in Data Science
at
Emeritus
Faculty details

Prof. Anjan Kumar Swain

Professor Swain has a PhD from the University of Sheffield, United Kingdom. His research interests include managerial implications of state-of-the-art methods of digital transformation, blockchain technology, artificial intelligence and other upcoming technologies. His publications are in the fields of mathematical modelling, Space Robotics, AI-based methods for decision-making, and multi-criteria decision-making, amongst others

Prof. M.P. Sebastian

Professor Sebastian received both his masters degree and PhD from the Indian Institute of Science, Bangalore. His research interests include artificial intelligence, machine learning, cybersecurity, healthcare ICT etc. He has published many research papers in reputed journals. He has guided many PhD candidates and is a reviewer for journals such as Nature Communications, International Journal of Medical Informatics, Government Information Quarterly among others.