Data Analytics and Visualisation
₹18000
About this course
This program will equip you with tools to combat real-world problems using data analytics and thus, refine day-to-day business decision making. You will learn applications of data analytics in marketing, product, retail & sales, customer research & insights, and digital marketing. By the end of the programme, you will acquire a data-driven analytical framework that will help you solve critical business challenges and spur career advancement. It will help you acquire the relevant analytical mindset to disrupt, innovate and scale your organisation’s business strategies for an improved ROI.
Course Video
Who can join
Early-stage professionals aspiring to strengthen their skills and establish a career in data analytics, product, sales, marketing, and branding domains;
Senior managers and leaders who want to acquire a nuanced understanding of the application of analytics to conceptualise superior business strategies;
Consultants who want to use the right mix of data analytics, insight and strategy to assist their clients in connecting the dots;
Entrepreneurs and business owners keen on driving customer-centric decision-making through practical data analytics strategies.
What you will get
What you will learn
Skills you will gain
Syllabus
Early-stage professionals aspiring to strengthen their skills and establish a career in data analytics, product, sales, marketing, and branding domains Senior managers and leaders who want to acquire a nuanced understanding of the application of analytics to conceptualise superior business strategies Consultants who want to use the right mix of data analytics, insight and strategy to assist their clients in connecting the dots Entrepreneurs and business owners keen on driving customer-centric decision-making through practical data analytics strategies"
Module 1
Data sources and analytics
Types of data: qualitative and quantitative/primary vs. secondary Use of various data collection techniques across various business domains Qualitative and quantitative data collection techniques (FGDs and Depth interviews) Use of various software for data analytics Introduction to R/IBM SPSS Data coding and preliminary data analysis Data cleaning and generating insights through graphics/Visualisation Generating insights through descriptive analytics
Module 2
Data mining and predictive modelling
Introduction to statistics and its applications using software Descriptive statistics and its applications Inferential statistics and test of hypothesis Supervised/unsupervised learning algorithms Regression Analysis Logistic Regression KNN Decision tree Random Forest Bagging and Boosting
Module 3
Data analytics and strategy formulation
Developing product introduction strategy Formulating the data driven pricing strategy Analyse profitability potential for new products Estimating the potential volume and new product demand Managing products with sustainable competitive advantage Expected profitability of newly acquired customers Customer level purchase information for customer retention Predicting customer churn Improving customer satisfaction through data driven insights Managing customer loyalty Understanding Customer Lifetime Value Recency, frequency, and monetary value (RFM) of customers Deciding the media strategy
Module 4
Data analytics for financial decisions
Fundamentals of Finance & Financial Analytics Data analytics for financial strategy formulation Financial modelling and Prediction Stock Price Forecasting Text mining for business insights