Analytics / Data Analytics Certification Training Course
In association with :
Certificate from prestigious IIT Madras Pravartak
Are you looking for a high-paying career? Your search ends here! India is in dire need of Data Analysts. ExcelR's Data Analyst Course trains you in the relevant tools and skills & prepares you for a secure job with our network of 4000+ hiring partners. Now, with the added advantage of IIT Madras Pravartak Certification.
15+ Hours of Immersive Training at IIT Madras for 2 days.
Interactive sessions by professors of IIT.
An industry-leading IITM Pravartak Certificate.
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Course Description
What does the course offer ?
The Data Analyst Course covers technologies like Excel, Advanced Excel, Tableau, SQL, Power BI, Basics of R & Python. Apart from the theory classes, there are hands-on assignments and projects that help you apply the concepts that are learnt by a student.
Advanced Certification Program in Data Science and AI for Digital Transformation from IITM Pravartak:
ExcelR, in association with IIT Madras, brings to you an add-on certification for your Data Science Course.
This certification program provides you with:
- 15+ Hours of Interactive Live-Virtual Sessions by professors of IIT Madras.
- Optional 2-day Campus Immersion in the beautiful, state-of-the-art IIT Madras.
- A prestigious IIT Madras Pravartak Certificate.
What is the certification process?
During the period of your course, interactive live-virtual sessions will be conducted by professors of IIT Madras. An optional campus immersion will also be planned, whereby a slot will be created, and you will travel to Chennai for a two-day experience at the IIT Madras campus. Post training, you will take a short quiz on the topics discussed in the session, which will unlock your Advanced Certification Program in Data Science and AI for Digital Transformation from IITM Pravartak.
Program Highlights
Top-Notch Faculty
Trainers at ExcelR are passionate about training, and carry 12+ years of industry experience.
Exhaustive Course Curriculum
Our industry-relevant course curriculum is tailored to provide practical exposure with the theory.
Real-life Projects and Bootcamps
Learners will work on real-life data analytics scenarios from various domains to get application knowledge.
Job Readiness
Intensive interview preparation from Day 1 to prepare candidates for interviews with our network of 2000+ hiring partners.
Skills Covered
Tools and Technologies
Data Analyst Project Life Cycle
Phase 1 - Data Collection
- After carefully evaluating the business case in a particular domain, data will be collected surrounding it.
Phase 2 - Data Preparation
- Using SQL, a database will be created to store the data collected in the previous step.
Phase 3 - Insights Generation and Dashboard Building
- Establish a connection between the database and Tableau/Python/R tools to extract the required data. Generate user-friendly reports according to the business needs and develop the dashboard using Tableau/Power BI.
Projects
Analysis of Patient Data (Domain: Healthcare)
- This project requires learners to analyze the patient data of those suffering from different diseases across various summaries. The facility, chain organizations, and dialysis stations analysis is required to be carried out where the patients are undergoing dialysis. The project also focuses on the payment mode aspect wherein if any discounts or reduction in payments have happened then those are analyzed.
Loan of Customers (Domain: Banking and Finance)
- In this project, learners analyze the loan given by a financial institution to different customers of varied grades and sub-grade levels. The analysis needs to consider the loan disbursement reasons, funded amount, and revolving balance values for every customer in different states and geolocations. The project requires the customers payment modes and the last payment values.
Employee Retention (Domain: HR analytics)
- This HR-related project considers the attrition rate of employees working at an organization at different levels. The attrition rate analysis is done with respect to different factors such as monthly income, last promotion year, job role, and work-life balance of every employee of different departments.
Industrial Combustion Energy Use (Domain: Energy)
- The project requires learners to analyze the usage of different fuels in different facilities in different applications by finding the MMBTu and GWHt values. The fuels used for different geo-locations and for different primary titles are also taken into consideration while doing analysis.
Flights delay analysis (Domain: Aviation)
- The primary aim of the project is to determine the different reasons behind the delay of flights of various airlines. The analysis needs to consider the number of flights in operation, the number of flights cancelled, and the statistical summary of week-wise, state-wise, and city-wise flight distributions.
Olist Store Analysis (Domain: eCommerce)
- The market for a certain product is analyzed by considering a particular retail outlet which sells these products. The project involves statistical analysis on the payment distribution from different customers with the different modes of transactions across different product categories. The feedback from customers with respect to shipping days and other factors also needs to be considered while carrying out the analysis.
Learning Path
Why ExcelR
Industry-Based Course Curriculum
Value Adds: Python Programming, Fundamentals of R, Business Statistics, SAS and ChatGPT
Work Hands-on With 50+ Labs, 30+ Assignments, and 1500+ Interview Preparation Questions
Dedicated Placement Cell
Support through WhatsApp, Calls & Emails
Lifetime eLearning Access
Course Curriculum
Topics to be covered
- Excel: Basics to Advanced
- MySQL
- Tableau
- Power BI
Excel
- 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
MySQL
- 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
- DML
- 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
Tableau
- 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
- 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
- Business Statistics
- Fundamentals of R
- Fundamentals of Python
- SAS(Self Paced)
- ChatGPT
Business Statistics
- 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
Fundamentals of R
- "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
Fundamentals of Python
- 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
ChatGPT
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
Contact Our Team of Experts
Why ExcelR?
Participants Placed Through ExcelR
Githin James
Anushri Agarwal
Apoorva
Avimanyu Basu
Bharat Kumar
Faraz
Gopal
Manasa
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Manohar
Nalini Khade
Yogesh
Rajeswar Rao
Vikram Arora
Vishal Dixit
Sushant
Swetha
Dinesh
Vasantha
Amit MG
Agarwal Subham
Murali
Nikhil
Teja
Saurabh Chawla
Prayash
Mihir
Shirin
Sayantan
Santhosh
Anup Harne
Nitin Mishra
Chetan Reddy Velma
Santosh Kumar Isukapalli
Tarakeshwari Junge
Naveen Reddy
Pavan
Rajashekar
Byl Lavanya
Saif
Nagaraj
Nagireddy
Venu
Raj
Sai Krishna
Neha
Swostiman
Hari
Pradeep
Sneha
Praveen
Bhagya Lakshmi
Saipriya
Midhun
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Madhavi
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Tanya
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Rohan
Bhavana Tangirala
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Alisha Kar
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Ruhi Ragini
Gopal
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Pragya
Rajan
Testimonials
FAQs
What Is JUMBO PASS?
- The all new and exclusive JUMBO PASS is the latest initiative taken by ExcelR to offer you access to attend unlimited batches over the duration of 365 days. You will be able to attend unlimited number of classes for the course of your choice.
What Is The Difference Between Data Analytics, Business Analytics And Data Science?
- Data Analytics, Business Analytics and Data Science are the same with just 3 different names. The name of the role of people working in this profession is called as Data Analyst
What if I have no experience in Data analytics?
- Data Analytics is a profession which caught the attention of the world only since 2 years. Because of this very reason most companies are struggling to close the demand-supply gap. Hence, people who are trained and have decent exposure to the data analytics techniques are recruited immediately.
What if I am a fresher? Can I still get a job in Data analytics?
- There are a lot of job opportunities in various job portals for freshers. The key thing employer would be keen to know is whether you have the conceptual knowledge or not. The projects provided by ExcelR in various concepts will only reinforce your learning to make you market ready for the jobs.
What if I forget the Data analytics concepts after attending the Data analytics training?
- We understand that the human brain can grasp only so much. Hence, we record all the sessions and provide access to the e-learning to the trainees for the rest of their life.
Do I need to have strong programming skills to be a data analyst?
- Yes and No. Yes in the sense programming skills would be required and No in the sense one need not have extremely strong programming skills. However, we at ExcelR ensure that you get sufficient exposure to the statistical programming tool called ‘R’. We start right from the basics assuming you do not have any exposure towards programming.
Why should we learn R? Can’t we learn any other tool for Data analytics?
- R has approximately 50% market share and it is open source (free of cost). Hence, R is very lucrative in the analytics space. Almost all the jobs are asking for experience and exposure in R. Demand for other statistical tools is decreasing steadily and hence it is recommended to be futuristic and invest time in learning R.
What are the salaries that we can expect in the profession of Data analytics?
- Salaries range varies based on experience, industry, domain, geography and various other parameters. However, as a general thumb rule, we can apply the following formula:
- Salary = No. of years of experience * 3 Lakhs per annum (India – INR)
- Salary = No. of years of experience * $1200 to $1500 per annum (Overseas – USD)
What Is Instructor-Led Online Training?
- Instructor-led online training is an interactive mode of training where participants and trainer will log in at the same time and live sessions will be done virtually. These sessions will provide scope for active interaction between you and the trainer.
How Many Batches Can I Attend, If Enrolled For Training?
- ExcelR offers a blended model of learning. In this model participants, can attend classroom, instructor-led live online and e-learning (recorded sessions) with a single enrolment. A combination of these 3 will produce a synergistic impact on the learning. One can attend multiple Instructor-led live online sessions for one year from different trainers at no additional cost with the all new and exclusive JUMBO PASS.
Is This A Live Training Or Recorded Sessions?
- The training is a live instructor-led interactive session done at a specific time where participants and trainer will log in at the same time. The same session will be also recorded and access will be provided to revise, recap or watch a missed session.
Whom Should I Contact If I Want to Know More Information About The Training?
- You can reach out to us by visiting our website and interact with our live chat support team. Our customer service representatives will assist you with all your queries.
What If I Miss A Live Session?
- Not a problem even if you miss a live Data Analytics session for some reason. Every session will be recorded and access will be given to all the videos on ExcelR’s state-of-the-art Learning Management System (LMS). You can watch the recorded Data Analytics sessions at your own pace and convenience.
Will I Get A Data Analytics Course Completion Certification From ExcelR?
- Yes, after successfully completing the course you will be awarded a course completion certificate from ExcelR.
What Are The Different Modes Of Payment Available?
- The different payment methods accepted by us are
- Cash
- Net Banking
- Cheque
- Debit Card
- Credit Card
- PayPal
- Visa
- Mastercard
- American Express
- Discover
Global Presence
ExcelR is a training and consulting firm with its global headquarters in Houston, Texas, USA. Alongside to catering to the tailored needs of students, professionals, corporates and educational institutions across multiple locations, ExcelR opened its offices in multiple strategic locations such as Australia, Malaysia for the ASEAN market, Canada, UK, Romania taking into account the Eastern Europe and South Africa. In addition to these offices, ExcelR believes in building and nurturing future entrepreneurs through its Franchise verticals and hence has awarded in excess of 30 franchises across the globe. This ensures that our quality education and related services reach out to all corners of the world. Furthermore, this resonates with our global strategy of catering to the needs of bridging the gap between the industry and academia globally.
