Data Analytics Master Course
6 Months Live Data Analyst Course | 2 Months Non-Paid Internship
160 Hours Lectures | 100+ Hours Practical Assignments | Hands On Tool Based Learning
Pay in 7 Interest-Free EMI For INR 8411/Month
7+ Live Projects | 10+ Case Studies | Master 7+ Tools
100% Assured Internship | Interview Guarantee
Data Analytics Master Certification From IIM SKILLS | Recognized by Govt of India
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3-8 LAC Average CTC
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Master Certification
Earn industry's most trusted Master's Certification in Data Analysis from IIM SKILLS.



100% Tools Driven Training
Learn to leverage high-end tools and technology to process Data Analytics efficiently.


Lifetime Access
Enjoy access to all the resource material, session recordings, and tools knowledge via Learning Management System throughout your lifetime.


24x7 Support
Get round-the-clock support from the IIM SKILLS team, ruling out all your worries and doubts


Practical Learning
Learn from the best in the industry with a 100% focus on practical acquisition. Become job-ready by the end of the course.
Course Deliverables of Our Refined Data Analytics Course
Core Modules
Subjects Covered
Course Content
Basic and Advance Excel
- Introduction to Excel Environment
- Formatting and Conditional Formatting
- Data Sorting, Filtering and Data Validation
- Understanding of Name Ranges
Data Visualisation in Excel
- Overview of chart types - column and bar charts, line and area charts, pie charts, doughnut charts, scatter plots
- How to select right chart for your data
- Chart formatting
- Creating and customizing advance charts - thermometer charts, waterfall charts, population pyramids
Data Manipulation using Functions
- Descriptive functions: sum, count, min, max, average, counta, countblank
- Logical functions: IF, and, or, not
- Relational operators > >= < <==!=
- Nesting of functions
- Date and Time functions: today, now, month, year, day, weekday, networkdays, weeknum, time, minute, hour
- Text functions: left, right, mid, find, length, replace, substitute, trim, rank, rank.avg, upper, lower, proper
- Array functions: sumif, sumifs, countif, countifs, sumproduct
- Use and application of lookup functions in excel: Vlookup, Hlookup
- Limitations of lookup functions
- Using Index, Match, Offset, concept of reverse vlookup
Data Analysis and Reporting
- Data Analysis using Pivot Tables - use of row and column shelf, values and filters
- Difference between data layering and cross tabulation, summary reports, advantages and limitations
- Change aggregation types and summarisation
- Creating groups and bins in pivot data
- Concept of calculated fields, usage and limitations
- Changing report layouts - Outline, compact and tabular forms
- Show and hide grand totals and subtotals
- Creating summary reports using pivot tables
Overview of Dashboards
- What is dashboard & Excel dashboard
- Adding icons and images to dashboards
- Making dashboards dynamic
Create dashboards in Excel - Using Pivot controls
- Concept of pivot cache and its use in creating interactive dashboards in excel
- Pivot table design elements - concept of slicers and timelines
- Designing sample dashboard using Pivot Controls
- Design principles for including charts in dashboards - do's and don’t's
Introducing VBA
- What is Logic?
- What Is VBA?
- Introduction to Macro Recordings, IDE
Key Components of Programming language
- Essential VBA Language Elements
- Keywords & Syntax
- Programming statements
- Variables & Data types
- Comments
- Operators
- Working with Range Objects
How VBA Works with Excel
- Working In the Visual Basic Editor
- Introducing the Excel Object Model
- Using the Excel Macro Recorder
- VBA Sub and Function Procedures
Programming constructs in VBA
- Control Structures
- Looping Structures
- The With- End with Block
Functions & Procedures in VBA - Modularizing your programs
- Worksheet & workbook functions
- Automatic Procedures and Events
- Arrays
Objects & Memory Management in VBA
- The NEW and SET Key words
- Destroying Objects - The Nothing Keyword
Communicating with Your Users
- Simple Dialog Boxes
- User Form Basics
- Using User Form Controls
- Add-ins
- Accessing Your Macros through the User Interface
- Retrieve information through Excel from Access Database using VBA
Others
- A look at some commonly used code snippets
- Error Handling
- Controlling accessibility of your code - Access specifier
- Code Reusability - Adding references and components to your code
Basics RDBMS Concepts
- Schema - Meta Data - ER Diagram
- Looking at an example of Database design
- Data Integrity Constraints & types of Relationships (Primary and foreign key)
- Basic concepts – Queries, Data types & NULL Values, Operators and Comments in SQL
Utilising The Object Explorer
- What is SQL - A Quick Introduction
- Installing MS SQL Server for windows OS
- Introduction to SQL Server Management Studio
- Understanding basic database concepts
- Getting started
Data Based Objects Creation (DDL Commands)
- Creating, Modifying & Deleting Databases and Tables
- Drop & Truncate statements - Uses & Differences
- Alter Table & alter Column statements
- Import and Export wizard to get the data in SQL server from excel files or delimited files
Data manipulation (DML Commands)
- Insert, Update & Delete statements
- Select statement – Subsetting, Filters, Sorting. Removing Duplicates, grouping and aggregations etc
- Where, Group By, Order by & Having clauses
- SQL Functions – Number, Text, Date, etc
- SQL Keywords – Top, Distinct, Null, etc
- SQL Operators - Relational (single valued and multi valued), Logical (and, or, not), Use of wildcard operators and wildcard characters, etc
SQL Server Reporting Services (6 Hours)
- Basics of SSRS
- Creating Parameters
- Understanding Visualisation
- Creating Visualisation using SSRS
SQL Server Integration Services (9 Hours)
- Understanding Basics of SSIS
- Understanding Packages
- Creating Packages to integrate
- Creating Project using SSIS
Others
- Accessing Data from Multiple Tables Using SELECT
- Append and Joins
- Union and Union All – Use & Constraints
- Intersect and Except statements
Table Joins - inner join, left join, right join, full join
- Cross Joins/Cartesian Products, Self Joins, Natural Joins etc
- Inline Views and Sub-queries
- Optimizing Your Work
Introduction
- Introduction to Power B
- Installing Power BI Desktop (Signup for PowerBI)
- Various Options in Power BI Desktop
- Views in Power BI Desktop
- Template Apps
- Task pipeline when your working on a project
Data Preparation and Modelling
- Connect and Retrieve data from different sources (csv, excel etc.)
- Query editor in Power BI
- Power Query for cleaning the data
- Power Query Functions – Text, Date, Numeric
- Power Query Conditional Columns
- Clean & transform data with Query Editor
- Define data granularity
- Combining data – Merging & Appending
- Fill Down in Power BI, Grouping, Transpose, Unpivot, Data Types, Replace errors and values,
Keep and Remove rows, Add Remove and Go To Columns
- Work with relationships and cardinality
- Types of Relationships (1:1, 1: Many, Many:1)
- Optimizing for performance
- PBIDS Files
Data Analysis Expressions (DAX)
- Work with relationships and cardinality
- Types of Relationships (1:1, 1: Many, Many:1)
- Optimizing for performance
- PBIDS Files
Reports Development (Visuals in Power BI)
- Introduction to work with Power BI visuals
- Reports Development in Power BI
- Working with Different Visuals /Charts
- Formatting Options in Reports
- Use a slicer to filter visualizations
- Working with Filters (Page Level, Include/Exclude, Report Level, Cross report Filter)
- Download & use Custom Visuals from the galary
- Add an R or Python visual
- Work with key performance indicators
- Project to Implement the learning's
Introduction to Basic Statistics
- Introduction to Statistics
- Measures of central tendencies
- Measures of variance
- Measures of frequency
- Measures of Rank
- Basics of Probability, distributions
- Conditional Probability (Bayes Theorem)
Introduction to Mathematical Foundations
- Introduction to Linear Algebra
- Matrices Operations
- Introduction to Calculus
- Derivatives & Integration
- Maxima, minima
- Area under the curve
- Theory of optimization
Introduction to Analytics & Data Science
- What is analytics & Data Science?
- Business Analytics vs. Data Analytics vs. Data Science
- Common Terms in Analytics
- Analytics vs. Data warehousing, OLAP, MIS Reporting
- Types of data (Structured vs. Unstructured vs. Semi Structured)
- Relevance of Analytics in industry and need of the hour
- Critical success drivers
- Overview of analytics tools & their popularity
- Analytics Methodology & problem-solving framework.
- Stages of Analytics
Python Essentials (Core)
- Overview of Python- Starting with Python
- Why Python for data science?
- Anaconda vs. python
- Introduction to installation of Python
- Introduction to Python IDE's(Jupyter,/Ipython)
- Concept of Packages - Important packages
- NumPy, SciPy, scikit-learn, Pandas, Matplotlib, etc
- Installing & loading Packages & Name Spaces
- Data Types & Data objects/structures (strings, Tuples, Lists, Dictionaries)
- List and Dictionary Comprehensions
- Variable & Value Labels – Date & Time Values
- Basic Operations – Mathematical/string/date
- Control flow & conditional statements
- Debugging & Code profiling
- Python Built-in Functions (Text, numeric, date, utility functions)
- User defined functions – Lambda functions
- Concept of apply functions
- Python – Objects – OOPs concepts
- How to create & call class and modules?
Operations With NumPy (Numerical Python)
- What is NumPy?
- Overview of functions & methods in NumPy
- Data structures in NumPy
- Creating arrays and initializing
- Reading arrays from files
- Special initializing functions
- Slicing and indexing
- Reshaping arrays
- Combining arrays
- NumPy Maths
Overview of Pandas
- What is pandas, its functions & methods
- Pandas Data Structures (Series & Data Frames)
- Creating Data Structures (Data import – reading into pandas)
Cleansing Data With Python
- Understand the data
- Sub Setting / Filtering / Slicing Data
- Using [] brackets
- Using indexing or referring with column names/rows
- Using functions
- Dropping rows & columns
- Mutation of table (Adding/deleting columns)
- Binning data (Binning numerical variables in to categorical variables)
- Renaming columns or rows
- Sorting (by data/values, index)
- By one column or multiple columns
- Ascending or Descending
- Type conversions
- Setting index
- Handling duplicates /missing/Outliers
- Creating dummies from categorical data (using get_dummies())
- Applying functions to all the variables in a data frame (broadcasting)
- Data manipulation tools(Operators, Functions, Packages, control structures, Loops, arrays etc.)
Data Analysis Using Python
- Exploratory data analysis
- Descriptive statistics, Frequency Tables and summarization
- Uni-variate Analysis (Distribution of data & Graphical Analysis)
- Bi-Variate Analysis(Cross Tabs, Distributions & Relationships, Graphical Analysis)
Basic Visualization Tools
- Area Plots
- Histograms
- Bar Charts
- Pie Charts
- Box Plots
- Scatter Plots
- Bubble Plots
Visualizing Geospatial Data
- Introduction to Folium
- Maps with Markers
- Choropleth Maps
Data Visualization With Python
- Introduction to Data Visualization
- Introduction to Matplotlib
- Basic Plotting with Matplotlib
- Line Plots
Advanced Visualization Tools
- Waffle Charts
- Word Clouds
- Seaborn and Regression Plots
Statistical Methods & Hypothesis Testing
- Descriptive vs. Inferential Statistics
- What is probability distribution?
- Important distributions (discrete & continuous distributions)
- Deep dive of normal distributions and properties
- Concept of sampling & types of sampling
- Concept of standard error and central limit theorem
- Concept of Hypothesis Testing
- Statistical Methods - Z/t-tests (One sample, independent, paired), ANOVA, Correlation and Chisquare
Getting Started
- What is Tableau? What does the Tableau product suite comprise of? How Does Tableau Work?
- Tableau Architecture
- Connecting to Data & Introduction to data source concepts
- Understanding the Tableau workspace
- Dimensions and Measures
- Data Types & Default Properties
- Tour of Shelves & Marks Card
- Using Show Me
- Saving and Sharing your work-overview
Data Handling & Summaries
- Date Aggregations and Date parts
- Cross tab & Tabular charts
- Totals & Subtotals
- Bar Charts & Stacked Bars
- Line Graphs with Date & Without Date
Data Handling & Summaries
- Tree maps
- Scatter Plots
- Individual Axes, Blended Axes, Dual Axes & Combination chart
- Edit axis
- Parts of Views
- Sorting
- Trend lines
- Reference Lines
- Forecasting
- Filters
- Context filters
- Sets
- In/Out Sets
- Combined Sets
- Grouping
- Bins/Histograms
- Drilling up/down – drill through
- Hierarchies
- View data
- Actions (across sheets)
Building Advanced Reports/ Maps
- Explain latitude and longitude
- Default location/Edit locations
- Building geographical maps
- Using Map layers
Table Calculations
- Explain scope and direction
- Percent of Total, Running / Cumulative calculations
- Introduction to LOD (Level of Detail) Expressions
- User applications of Table calculations
Calculated Fields
- Working with aggregate versus disaggregate data
- Explain - #Number of Rows
- Basic Functions (String, Date, Numbers etc)
- Usage of Logical conditions
Data Importing/Exporting
- Introduction R/R-Studio - GUI
- Concept of Packages - Useful Packages (Base & Other packages)
- Data Structure & Data Types (Vectors, Matrices, factors, Data frames, and Lists)
- Importing Data from various sources
- Exporting Data to various formats
- Viewing Data (Viewing partial data and full data)
- Variable & Value Labels – Date Values
Data Manipulation
- Creating New Variables (calculations & Binning)
- Dummy variable creation
- Applying transformations
- Handling duplicates/missing's
- Sorting and Filtering
- Sub setting (Rows/Columns)
- Appending (Row/column appending)
- Merging/Joining (Left,right,inner,full,outer)
- Data type conversions
- Renaming
- Formatting
Data Manipulation
- Reshaping data
- Sampling
- Operators
- Control Structures (if, if else)
- Loops (Conditional, iterative loops)
- Apply functions
- Arrays
- R Built-in Functions
- Text, Numeric, Date, utility
- R User Defined Functions
- Aggregation/Summarization
Data Analysis
- Introduction exploratory data analysis
- Descriptive statistics, Frequency Tables and summarization
- Uni-variate Analysis (Distribution of data)
- Bivariate Analysis(Cross Tabs, Distributions & Relationships)
Data Visualization with R
- Basic Visualization Tools
- Bar Charts/Histograms/Pie Charts
- Scatter Plots
- Line Plots and Regression
- Specialized Visualization Tools
- Word Clouds/ Radar Charts
- Waffle Charts/ Box Plots
- How to create Maps
- Creating Maps in R
- How to build interactive web pages
- Introduction to Shiny
- Creating and Customizing Shiny Apps
- Additional Shiny Features
Using R with Databases
- R and Relational Databases
- Connecting to Relational Databases using RJDBC and RODBC
- Database Design and Querying Data
- Modifying Data and Using Stored Procedures
- In-Database Analytics with R
Introduction to Statistics
- Basic Statistics - Measures of Central Tendencies and Variance
- Building blocks - Probability Distributions – Normal distribution - Central Limit Theorem
- Inferential Statistics -Sampling - Concept of Hypothesis
Linear Regression: Solving Regression Problems
- Introduction - Applications
- Assumptions of Linear Regression
- Building Linear Regression Model
- Understanding standard metrics (Variable significance, R-square/Adjusted R-square, Global hypothesis ,etc)
- Assess the overall effectiveness of the model
- Validation of Models (Re running Vs. Scoring)
- Standard Business Outputs (Decile Analysis, Error distribution (histogram), Model equation, drivers etc.)
- Interpretation of Results - Business Validation - Implementation on new data
Testing
- Statistical Methods - Z/t-tests (One sample, independent, paired), Anova, Correlations and Chisquare
Data Analytics Using Alteryx
- Overview of the Alteryx course and fundamental concepts
- Using the Select tool to rename fields, change the data type
- Understanding the User Environment and Alteryx Settings
- Remove from data set
- Understanding Alteryx Designer
- Connect to data sources
- Alteryx designer Interface
- Set data field types
- User and Workflow settings
- Remove and rename fields
- Filtering Data/Data processing
- S Blending/Join Data from Different Sources
- Filtering Using String Data
- Find customer with 10 or more transactions
- Input Data, Dynamic Rename, Text to columns, Transpose
- Identify common data fields
- See how all records fit the filter
- Data Cleansing
- Impute Values
- Random Sample