Diploma in Analytics in Kolkata

Gain a substantial understanding of business analytics
Install R, R-studio, and workspace setup, and learn about the various R packages
Master R programming and understand how various statements are executed in R
Gain an in-depth understanding of data structure used in R and learn to import/export data in R
Define, understand and use the various apply functions and dplyr functions
Understand and use the various graphics in R for data visualization
Gain a basic understanding of various statistical concepts
Understand and use hypothesis testing method to drive business decisions
Understand and use linear, non-linear regression models, and classification techniques for data analysis
Learn and use the various association rules and Apriori algorithm Learn and use clustering methods including K-means, DBSCAN, and hierarchical clustering

• Introduction to Business Analytics
• Introduction to R Programming
• Data Structures
• Data Management in R
• Advanced Data Visualization
• Descriptive Statistics in R
• Regression Analysis
• Decision Tree: Classification
• Clustering: K-means and Hierarchical
• Association Rule Analysis

- Learn an in-depth understanding of Data Science processes, data wrangling, data exploration, datvisualization, hypothesis building, and testing Install the required - Understand Python environment and other auxiliary tools and libraries - Understand the essential concepts of Python programming such as data types, tuples, lists, dicts,basic operators, and functions - Perform high-level mathematical computing using the NumPy package and its vast library ofmathematical functions - Carry out scientific and technical computing using the SciPy package and its sub-packages such as Integrate, Optimize, Statistics, IO, and Weave - Carry out data analysis and manipulation using data structures and tools provided in the Pandaspackage - Gain an in-depth understanding of supervised learning and unsupervised learning models such as linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline - Use the Matplotlib library of Python for data visualization - Extract useful data from websites by performing web scraping using Python

• Data Science Overview
• Data Analytics Overview
• Statistical Analysis and Business Applications
• Python Environment Setup and Essentials
• Mathematical Computing with Python (NumPy)
• Scientific Computing with Python (Scipy)
• Data Manipulation with Pandas

Learn about math, variables, and strings, vectors, factors, and vector operations
Gain fundamental knowledge on arrays and matrices, lists, and data frames
Get an understanding of conditions and loops, functions in R, objects, classes, and debugging
Learn how to accurately read the text, CSV, and Excel files. Learn how to write and save data objects in R to a file
Understand the working of strings and dates in R

• R Basics
• Data Structures in R
• R Programming Fundamentals
• Working with Data in R
• Handling Data in R

Start creating the First Python program by implementing concepts of variables, strings, functions, loops, conditions
Understand the modulation of lists, sets, dictionaries, conditions and branching, objects and classes
Work with data in Python such as reading and writing files, loading, working, and saving data with Pandas

• Python Basics
• Python Data Structures
• Python Programming Fundamentals
• Working with Data in Python
• Working with NumPy Arrays

Master Business Intelligence using Power BI
Create Powerful Storylines Presentation to Executives
Develop Intrinsic Understanding of How Table Calculations Work
Create Effective Presentations using Stories
Easily Implement Advanced Mapping Techniques
Understand Data/KPIs and Importance of Business Intelligence
Create Highly Interactive Dashboards
Easily Create Charts of any Type

• Business Intelligence (BI) Concepts
• Microsoft Power BI (MSPBI) Introduction
• Connecting Power BI with Different Data Sources
• Power Query for Data Transformation
• Data Modelling in Power BI
• Reports in Power BI
• Reports & Visualization Types in Power BI
• Dashboards in Power BI
• Data Refresh in Power BI
• Projects — End to End Data Modelling & Visualization

Master Data Visualization using Tableau
Create Powerful Storylines Presentation to Executives
Develop Intrinsic Understanding of How Table Calculations Work
Create Effective Presentations using Stories
Easily Implement Advanced Mapping Techniques
Understand Data/KPIs and the Importance of Data Visualization
Create Highly Interactive Dashboards
Easily Create Charts of any Type
Connect Tableau to other Sources effortlessly
Work on Real Life Business Problems Proficiently

• Introduction to Data Visualization and Power of Tableau
• Architecture of Tableau
• Working with Metadata and Data Blending
• Creation of Sets
• Working with Filters
• Organizing Data and Visual Analytics
• Working with Mapping Preview
• Working with Calculations and Expressions
• Working with Parameters Preview
• Charts and Graphs
• Dashboards and Stories
• Tableau Prep
• Integration of Tableau with R and Hadoop

Learn about SQL and its Installation.
Gain knowledge about Relational Databases, SQL Commands, and Statements.
Be Aware of JOIN; Inner, Left, Right, Full Outer, and Cross JOIN.
Learn about String Functions of SQL
Develop an understanding of Mathematical Functions of SQL
Understand DataTime functions of SQL, inclusive of Date and Time and Age functions

• SQL Overview
• SQL Manipulation
• JOIN
• String Functions
• Mathematical Functions
• Date-Time Functions
• Tuning Tips

Gain basic knowledge of MS Excel
Work flawlessly with the Basic Excel Function
Understand the Advanced Excel Functions and work with it
Get introduced to Lookup Functions
Learn the essential functions of Excel and the Pivot Table
Know the basics of VBA and its analysis
Acquire knowledge about Power Query and User-Defined Functions
Get Acquainted with the Basics of Advanced Excel
Acquire Knowledge of Advanced VBA
Learn to work with Advanced Excel Functions

• Introduction to MS Excel
• Working with Basic Excel Functions
• Understanding Advanced Excel Functions
• Introduction to Lookup Functions
• Pivot Table and Essential Functions of Excel
• Basic of VBA and What-If Analysis
• Power Query and User-Defined Functions
• Advanced Excel Functions
• Advanced VBA
• Advanced Excel

Learn about Data Processing and Data Cleaning: You will learn how to handle the data set and manage it with analytical tools
Applying the correct Models for the projects: Applying all the techniques learnt by understanding the data
Representing Results: You will be able to write report and represent the outcome of your analysis

• Retail (Actionable insights for improving sales of a consumer durables retailer using POS data analytics)
Market Basket Analysis, RFM (Recency, Frequency, Monetary) Analysis, Time Series Forecasting
• E-commerce (Customer engagement and brand perception of Indian ecommerce and social media approach)
Text Mining, K Means Clustering, Regression Trees, XGBoost, Neural Network
• Web & Social Media (Trapping Social Media exchanges on Twitter)
• Banking (Customer engagement and brand perception of Indian e commerce- A social media approach)
Linear Discriminant Analysis, Logistic Regression, Neural Network, Boosting, Random Forest, CART
• Insurance (Personal insurance digital assistant)
NLP (Natural Language Processing), Vector Space Model, Latent Semantic Analysis
• Entrepreneurship /Startups(Start-up insights through data analysis)
Univariate and Bivariate Analysis, Multinomial Logistic Regression, Random Forest
• Finance & Accounts(Vendor invoicing grief project)
Conditional Inference Tree, Logistic Regression, CART and Random Forest