Data Analyst Course

Data Analyst Course in Pune

Master the skills to excel in Pune's fast-paced business environment and lead the tech revolution!

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15,213
Students Enrolled

4.8
Google Reviews

6 Months
Duration

220+ Hours
of Learining

Job
Readiness

Course Overview

Pune: A Great Place for Data Analytics Training

Pune is home to numerous startups and established companies, making it a key player in India’s tech landscape. The city has a thriving IT sector and a growing demand for skilled data professionals, so a data analyst course in Pune is becoming increasingly valuable.

Our Course Highlights

150+ Hours of Learning

An expert-led training covering various aspects of data analytics

Jumbo Pass

Access unlimited live online batches from multiple trainers for 365 days

80+ Assignments

Develop concrete understanding with module-wise assignments and case studies

5 Capstone Projects

Get hands-on with guided projects built around real-world data

Post-Training Support

Get practice assistance from a dedicated team for assignments and projects

5 Value-Added Courses

Basics of R, Python, Business Statistics, ChatGPT, Introduction to SAS

Placement Prep

Placement Assistance with 5000+ Hiring Partners

Learning Path

Tools and Technologies

Excel(Basic & Advanced)

MySQL

Tableau

Power BI

Business Statistics

Python & R Programming

Large Language Models(LLM)&ChatGPT

SAS(Self Paced)

Skills covered

Data Analysis Concept

Data Base Concepts

Data Visualization

Function Charts and Slicers

Course Curriculum

  • Excel: Basics to Advanced
  • MySQL
  • Tableau
  • Power BI
  • Introduction
    • MS office Versions(similarities and differences)
    • Interface(latest available version)
    • Row and Columns
    • Keyboard shortcuts for easy navigation
    • Data Entry(Fill series)
    • Find and Select
    • Clear Options
    • Ctrl+Enter
    • Formatting options(Font,Alignment,Clipboard(copy, paste special))
  • Referencing, Named ranges,Uses,Arithemetic Functions
    • Mathematical calculations with Cell referencing(Absolute,Relative,Mixed)
    • Functions with Name Range
    • Arithmetic functions(SUM,SUMIF,SUMIFS,COUNT,COUNTA,COUNTIFS,AVERAGE,AVERAGEIFS,MAX,MAXIFS,MIN,MINIFS)
  • Logical functions
    • Logical functions:IF,AND,OR,NESTED IFS,NOT,IFERROR
    • Usage of Mathematical and Logical functions nested together
  • Referring data from different tables: Various types of Lookup, Nested IF
    • LOOKUP
    • VLOOKUP
    • NESTED VLOOKUP
    • HLOOKUP
    • INDEX
    • INDEX WITH MATCH FUNCTION
    • INDIRECT
    • OFFSET
  • Advanced functions
    • Combination of Arithmatic
    • Logical
    • Lookup functions
    • Data Validation(with Dependent drop down)
  • Date and Text Functions
    • Date Functions:DATE,DAY,MONTH,YEAR,YEARFRAC,DATEDIFF,EOMONTH
    • Text Functions:TEXT,UPPER,LOWER,PROPER,LEFT,RIGHT,SEARCH,FIND,MID,TTC, Flash Fill
  • Data Handling::Data cleaning, Data type identification, Remove Duplicates, Formatting and Filtering
    • Number Formatting(with shortcuts)
    • CTRL+T(Converting into an Excel Table)
    • Formatting Table
    • Remove Duplicate
    • SORT
    • Advanced Sort
    • FILTER
    • Advanced Filter
  • Data Visualization: Conditional Formatting, Charts
    • Conditional formatting(icon sets/Highlighted colour sets/Data bars/custom formatting)
    • Charts:Bar,Column,Lines,Scatter,Combo,Gantt,Waterfall,pie
  • Data Summarization: Pivot Report and Charts
    • Pivot Reports:Insert,Interface,Crosstable Reports;Filter,Pivot Charts,
    • Slicers:Add,Connect to multiple reports and charts
    • Calculated field, Calculated item
  • Data Summarization: Dashboard Creation, Tips and Tricks
    • Dashboard:Types,Getting reports and charts together, Use of Slicers.
    • Design and placement: Formatting of Tables,Charts,Sheets,Proper use of Colours and Shapes
  • Connecting to Data: Power Query, Pivot, Power Pivot within Excel
    • Power Query: Interface, Tabs
    • Connecting to data from other excel files, text files, other sources
    • Data Cleaning
    • Transforming
    • Loading Data into Excel Query
  • Connecting to Data: Power Query, Pivot, Power Pivot within Excel
    • Using Loaded queries
    • Merge and Append
    • Insert Power Pivot
    • Similarities and Differences in Pivot and Power Pivot reporting
    • Getting data from databases, workbooks, webpages
  • VBA and Macros
    • View Tab
    • Add Developer Tab
    • Record Macro:Name,Storage
    • Record Macro to Format table(Absolute Ref)
    • Format table of any size(Relative ref)
    • Play macro by button
    • shape
    • as command(in new tab)
    • Editing Macros
    • VBA:Introduction to the basics of working with VBA for Excel: Subs, Ranges, Sheets
    • Comparing values and conditions
    • if statements and select cases
    • Repeat processes with For loops and Do While or Do Until Loops
    • Communicate with the end-user with message boxes and take user input with input boxes, User Form
  • Introduction to Mysql
    • Introduction to Databases
    • Introduction to RDBMS
    • Explain RDBMS through normalization
    • Different types of RDBMS
    • Software Installation(MySQL Workbench)
  • SQL Commands and Data Types
    • Types of SQL Commands (DDL,DML,DQL,DCL,TCL) and their applications
    • Data Types in SQL (Numeric, Char, Datetime)
  • DQL & Operators
    • SELECT
    • LIMIT
    • DISTINCT
    • WHERE AND
    • OR
    • IN
    • NOT IN
    • BETWEEN
    • EXIST
    • ISNULL
    • IS NOT NULL
    • Wild Cards
    • ORDER BY
  • Case When Then and Handling NULL Values
    • Usage of Case When then to solve logical problems and handling NULL Values (IFNULL, COALESCE)
  • Group Operations & Aggregate Functions
    • Group By
    • Having Clause
    • COUNT
    • SUM
    • AVG
    • MIN
    • MAX
    • COUNT String Functions
    • Date & Time Function
  • Constraints
    • NOT NULL
    • UNIQUE
    • CHECK
    • DEFAULT
    • Primary key
    • Foreign Key (Both at column level and table level)
  • Joins
    • Inner
    • Left
    • Right
    • Cross
    • Self Joins
    • Full outer join
  • DDL
    • Create
    • Drop
    • Alter
    • Rename
    • Truncate
    • Modify
    • Comment
  • DML & TCL Commands
    • DML
      • Insert
      • Update & Delete
    • TCL
      • Commit
      • Rollback
      • Savepoint
      • Data Partitioning
  • Indexes and Views
    • Indexes (Different Type of Indexes)
    • Views in SQL
  • Stored Procedures
    • Procedure with IN Parameter
    • Procedure with OUT parameter
    • Procedure with INOUT parameter
  • Function, Constructs
    • User Define Function
    • Window Functions
    • Rank
    • Dense Rank
    • Lead
    • Lag
    • Row_number
  • Union, Intersect, Sub-query
    • Union, Union all
    • Intersect
    • Sub Queries, Multiple Query
  • Exception Handling
    • Handling Exceptions in a query
    • CONTINUE Handler
    • EXIT handler
  • Triggers
    • Triggers - Before | After DML Statement
  • Introduction to Tableau
    • What is Tableau ?
    • What is Data Visulaization ?
    • Tableau Products
    • Tableau Desktop Variations
    • Tableau File Extensions
    • Data Types, Dimensions, Measures, Aggregation concept
    • Tableau Desktop Installation
    • Data Source Overview
    • Live Vs Extract
  • Basic Charts & Formatting
    • Overview of worksheet sections
    • Shelves
    • Bar Chart, Stacked Bar Chart
    • Discrete & Continuous Line Charts
    • Symbol Map & Filled Map
    • Text Table, Highlight Table
    • Formatting: Remove grid lines, hiding the axes, conversion of numbers to thousands, millions, Shading, Row divider, Column divider
    • Marks Card
  • Filters
    • What are Filters ?
    • Types of Filters
    • Extract, Data Source, Context, Dimension, Measure, Quick Filters
    • Order of operation of filters
    • Cascading
    • Apply to Worksheets
  • Calculations
    • Need for calculations
    • Types: Basic, LOD's, Table
    • Examples of Basic Calculations: Aggregate functions, Logical functions, String functions, Tablea calculation functions, numerical functions, Date functions
    • LOD's: Examples
    • Table Calculations: Examples
  • Data Combining Techniques
    • What is Data Combining Techniques ?
    • Types
    • Joins, Relationships, Blending & Union
  • Custom Charts
    • Dual Axis
    • Combined Axis
    • Donut Chart
    • Lollipop Chart
    • KPI Cards (Simple)
    • KPI Cards (With Shape)
  • Groups, Bins, Hierarchies, Sets, Parameters
    • What are Groups ? Purpose
    • What are Bins ? Purpose
    • What are Hierarchies ? Purpose
    • What are Sets ? Purpose
    • What are Parameters ? Purpose and examples
  • Analytics & Dashboard
    • Reference Lines
    • Trend Line
    • Overview of Dashboard: Tiled Vs Floating
    • All Objects overview, Layout overview
    • Dashboard creation with formatting
  • Dashboard Actions & Tableau Public
    • Actions: Filter, Highlight, URL, Sheet, Parameter, Set
    • How to save the workbook to Tableau Public website ?
  • Power BI Introduction and Installation
    • Understanding Power BI Background
    • Installation of Power BI and check list for perfect installation
    • Formatting and Setting prerequisits
    • Understanding the difference between Power BI desktop & Power Query
  • The Power BI user interface, including types of data sources and visualizations
    • Getting familiar with the interface BI Query & Desktop
    • Understanding type of Visualisation
    • Loading data from multiple sources
    • Data type and the type of default chart on drag drop.
    • Geo location Map integration
  • Sample dashboard with Animation Visual
    • Finanical sample data in Power BI
    • Preparing sample dashboard as get started
    • Map visual Types and usages in different variation
    • Understanding scatter Plot chart with Play axis and the parameters
  • Power BI artificial intelligence Visual
    • Understanding the use of AI in power BI
    • AI analysis in power bi using chart
    • Q&A chat bot and the use in real life
    • Hirarchy tree
  • Power BI Visualization
    • Understanding Column Chart
    • Understanding Line Chart
    • Implementation of Conditional formating
    • Implementation of Formating techniques
  • Power Query Editor
    • Loading data from folder
    • Understanding Power Query in detail
    • Promote header, Split to limiter, Add columns, append, merge queries etc
  • Modelling with Power BI
    • Loading multiple data from different format
    • Understanding modelling (How to create relationship)
    • Connection type, Data cardinality, Filter direction
    • Making dashboard using new loaded data
  • Power Query Editor Filter Data
    • Power Query Custom Column & Conditional Column
    • Manage Parameter
    • Introduction to Filter and types of filter
    • Trend analysis, Future forecast
  • Customize the data in Power BI
    • Understanding Tool tip with information
    • Use and understanding of Drill Down
    • Visual interaction and customisation of visual interaction
    • Drill through function and usage
    • Button triggers
    • Bookmark and different use and implementation
    • Navigation buttons
  • Dax Expressions
    • Introduction to DAX
    • Table Dax, Calculated column, DAX measure and difference
    • Eg:- Calendar, Calendar auto, Summarize, Group by etc
    • Calculated Column
    • Related, Lookup value, switch, Datedif,Rankx,Date functions
    • Dax Measure and Quick Measure
    • Remove filters, Keep filters, All, Allselected, Time Intelligence Functions,Rolling average,YoY, Running total
  • Custom Visual
    • Custom visual and understanding the use of custom
    • Loading custom visual, Pinning visual
    • Loading to template for future use
    • Publishinhg Power Bi
  • Power BI Service
    • Introduction to app.powerbi.com
    • Schedule refresh
    • Data flow and use power bi from online
    • Download data as live in power point and more

Value Added Courses

  • Descriptive Statistics
    • Data Types, Measure Of central tendency, Measures of Dispersion
    • Graphical Techniques, Skewness & Kurtosis, Box Plot
  • Probability and Normal Distribution
    • Random Variable, Probability, Probility Distribution, Normal Distribution, SND, Expected Value
  • Inferential Statistics
    • Sampling Funnel, Sampling Variation, Central Limit Theorem, Confidence interval
    • Introduction to Hypothesis Testing
    • Hypothesis Testing (2 proportion test, 2 t sample t test)
    • Anova and Chisquare
  • Data cleaning and Insights
    • Data Cleaning(Invalid cells,Blanks,Outliers,Null values)
    • Imputation Techniques(Mean and Median)
    • Scatter Diagram
    • Correlation Analysis
  • "Introduction to R,Installation of Rstudio,Data Types in R
    • Data types(Numeric,Char,Logical,Complex,Vector,List,Matrix,Factor,Array,Dataframe),Relational operators,Logical operators
  • Decision making statements,Loops,Functions
    • If,Ifelse,For loop,While loop,Repeat,Functions
  • Built in Functions in R,Joins,dplyr and ggplot2
    • Merging dataframes,Analyzing Iris Dataset using apply functions,dplyr package(Filter,Sel,Arrange),Data visualization using ggplot2,Scatterplot,Histogram,Boxplot
  • Anaconda Installation,Introduction to python,Data types,Opearators
    • Variables,data types(integer,Boolean,Float,List,tuple,string),Opearators in python
  • Data types Contd,Slicing the data,Inbuilt functions in python
    • Dictionaries,Sequence methods,Concatenate,Repetition,len,min,max functions,Index position,Addition and deletion of elements,Reverse,Sorting
  • Sets,Set Theory,Regular Expressions,Decision making statements
    • Sets,re module(findall,search,split,match),if,elifGetting input from user,Identity Operators
  • Loops,Functions,Lambda functions,Modules
    • For,While loops,Functions,Lambda functions,Math module,Calender module,Date & time module
  • Pandas,Numpy,Matplotlib,Seaborn
    • Data frame creation using different methods,Using Pandas anlysis on Universities,Salary data sets,Visualization using Matplotlib and Seaborn,Numpy introduction

Introduction to ChatGPT and AI

  • What is ChatGPT?
  • The history of ChatGPT
  • Applications of ChatGPT
  • ChatGPT vs other chatbot platforms
  • Industries using ChatGPT
  • The benefits and limitations of ChatGPT
  • Future developments in ChatGPT technology
  • Ethical considerations related to ChatGPT and AI

Types of AI and Chatgpt architecture

  • What is AI?
  • Types of AI
  • What is Machine Learning?
  • Neural Networks
  • Deep Learning
  • Natural Language Processing (NLP)
  • Computer Vision
  • Robotics and AI

ChatGPT Functionalities and Applications

  • How does ChatGPT work?
  • ChatGPT Functionalities
  • Drafting emails and professional communication
  • Automating content creation
  • Resume and Cover letter creation
  • Research and information gathering
  • Brainstorming ideas and creative problem solving
  • Best Practices for Using ChatGPT

ChatGPT Prompt Engineering

  • What is Prompt Engineering?
  • Types of Prompts
  • Crafting Effective Prompts
  • Using ChatGPT to generate prompt

Career Progression and Salary Trends:

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Frequently Asked Questions

Our data analyst classes in Pune run for 6 months, featuring 150+ hours of comprehensive training. With a mix of theory and practical application, you'll be job-ready upon completion!
You can opt for either classroom or live online sessions, both designed to offer interactive and engaging learning experiences. Choose the format that suits your needs!
No problem! We provide access to recorded sessions, so you can catch up on any missed class at your convenience.
Absolutely! Our data analyst classes in Pune are perfect for freshers. We’ll start from the basics and guide you through each step, ensuring you build a strong foundation in data analytics.
Yes, our data analytics course in Pune is designed for career changers. If you’re looking to transition into the world of data analytics, we’ll equip you with the skills and knowledge to make that switch successfully.
Yes, you can! We focus on essential tools like Excel and SQL, which don’t require extensive coding knowledge, making the course accessible for beginners.
Yes, we do! With over 5000 hiring partners, our placement assistance program will help you prepare for interviews and connect you with top companies in the industry.

Data Science

Bangalore, Hyderabad, Mumbai, Pune

Data Analyst

Bangalore, Hyderabad, Mumbai, Pune

ExcelR Data Science Location in Bangalore Data Science, Data Analyst and Business Analyst Course in Pune

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Phone: 09513259011
Opening Hours: 24 hours

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