Get updates on Eligibility, Admission, Placements Fees Structure
Quick Facts
| Medium Of Instructions | Mode Of Learning | Mode Of Delivery |
|---|---|---|
| English | Self Study, Virtual Classroom | Video and Text Based |
Course Overview
The Certified Business Analytics/Data Science Course Training Programme provided by ExcelR imparts skills and knowledge to the participants in various concepts like basic statistics, ensemble techniques, model validation methods, probability, linear regression, logistic regression, association rules, decision tree, neural networks, text mining and natural language processing.
This Certified Business Analytics/Data Science Course Training Programme classes help the candidate to gain hands-on experience by providing various assignments and case studies. This programme is a blend of case studies, theory and projects. Apart from the main content, value added contents are provided additionally. Basic concepts in Python, R, MySQL, Artificial intelligence, Hadoop and Spark are taught in brief.
The certification provided at the end of the Certified Business Analytics/Data Science Course Training stands as a proof for the candidate’s skills. The participant will receive a dual certificate from ExcelR and Steinbeis University. On completion of the programme, the candidate would also yield an alumni status of SGIT. This Certified Business Analytics/Data Science online programme redefines the career of the candidate in the analytics domain.
The Highlights
- E-learning
- Post-training support
- Lifetime access to videos
- Placement assistance is provided
- Course curriculum designed by Steinbeis University
- Classroom programme and self-paced programme available
- Blended training model
- 6 months duration programme
- Recorded sessions are also available
- Alumnus status from SGIT, Steinbeis university
- Certificate from Steinbeis University
Programme Offerings
- Video sessions
- assignments
- Project works
- interview preparation.
Courses and Certificate Fees
| Certificate Availability | Certificate Providing Authority |
|---|---|
| yes | Steinbeis Global Institute, Tubingen |
The fee details of the Certified Business Analytics/Data Science Course Training Programme by ExcelR is given below
The cost of the live virtual classroom programme is ₹ 75,999
Certified Business Analytics Data Science Course Training Program in Delhi Fees Structure
Course type | Amount in INR |
Live virtual classroom programme | ₹ 75,999 |
Eligibility Criteria
Certification Qualifying Details
The participants are provided with the dual certificate from Steinbeis Akademie, Steinbeis University and ExcelR on successful completion of the Certified Business Analytics/Data Science Course Training Programme. The candidate must meet the qualification criteria provided by the university and also pass the exam by scoring more than 60% marks to receive the certificate. Only the candidates who are attending the virtual classroom programme are provided with the certificate. The candidate has to pay an additional fee for receiving the certificate.
What you will learn
The learner will understand the concepts which are given below by pursuing the Certified Business Analytics / Data Science Course Training Programme by ExcelR.
- Gain knowledge in data analytics and project life cycle
- Understand concepts in probability and hypothesis testing
- Learn principles of regression
- The participant would also learn about the components in linear regression with examples
- Understand the probability measures and their application
- Learn deployment in R using Shiny and Streamlit
- Get introduced to various types of linkages and clustering algorithms
- Learn the regularization techniques like ridge regression and lasso regression
- The classification which is done using Bayesian modelling and Naive bytes
- Understand the applications of Natural language processing
Who it is for
The following professionals can attend this Certified Business Analytics/Data Science Course Training Programme to enhance their career opportunities
- Mathematicians
- Business Analyst
- Economists
- Six sigma consultants
- Statisticians
- Candidates who are working on reporting tools and Business Intelligence
- Participants who are working on Data Warehouse Technologies
- Freshers
- Software programmers
Admission Details
The admission details for the Certified Business Analytics/Data Science Course Training Programme by ExcelR is given below
Step 1: Visit the url https://www.excelr.com/business-analytics-training-in-delhi
Step 2: The candidate has to create an account using email ID.
Step 3: The candidate has to choose the Certified Business Analytics/Data Science Course Training Programme and select either live virtual classroom or self-paced learning
Step 4: The candidate has to click “enrol now” in live virtual classroom or “Buy now” in self-paced learning
Step 5: The candidate can select their preferred batch details and enter coupon code and click “proceed” to continue the process.
Step 6: Then the personal details of the candidate has to be entered and the candidate should click “Proceed”
Step 7: After completing the payment process, the candidate can start the course.
The Syllabus
- 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
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
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 Agile
- Project Definition
- Difference Between Traditional & Agile Project Mgmt.
- Agile Manifesto and Principles
- Agile Methodology
- Agile Principles
- Agile Frameworks and Terminology
Agile Methodologies
- Scrum
- XP
Agile Analysis and Design
- Product Roadmap
- Product Backlog
- Story Maps
- Agile Modeling
- Wireframes
- Charting
- Personas
Planning and Monitoring
- Iteration and Release Planning
- Progressive Elaboration
- Time Boxing
- Cumulative Flow Diagram
- Kanban Boards
- WIP Limits
- Burn Charts
- Retrospectives
- Innovation Games
Agile Metrics and Estimations
- Relative Sizing
- Story Points
- Wideband Delphi Technique
- Planning Poker
- Affinity Diagram
- Ideal time
- Velocity
- Cycle Time
- EVM
- Escaped Defects
Quality
- Frequent Verification and Validation
- Test Driven Development
- Definition of Done
- Continues Integration
- Feedback Techniques
- Incremental Delivery
- Continuous Improvement
Value Based Prioritization
- Customer Valued Prioritization
- Compliance
- Relative Prioritization
- Value Stream Mapping
- Minimum Marketable Feature
Risk Management
- Risk Adjusted backlog
- Risk Burn down charts
- Risk based spike
Agile Communications
- Team Space
- Information Radiator
- Agile Tooling
- Daily Stand-ups
- Osmotic Communication
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
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
Steinbeis University, Berlin Frequently Asked Questions (FAQ's)
Instructor-led online training is a training mode where the instructors and participants will log in at the same timing and the sessions will be held online. These sessions provide better interaction between the trainer and the participant.
Yes, both live training and recorded sessions are available. Recorded sessions are provided for the candidate to access the course if they missed watching a session.
Yes, Certified Business Analytics/Data Science Course completion certificate is provided on successful completion of the course. The candidate has to score 60% marks in final exam to avail certificate.
Jumbo pass is an initiative taken by ExcelR to offer access to the candidate to attend unlimited batches for one year. The candidate can attend unlimited classes of their own choice.
The duration of the program is 6 months. The candidate is provided with live sessions, assignments and projects that would help them to gain more knowledge.
Professionals who are working in Data warehouse technologies and business intelligence, Statisticians, Mathematicians, Economists, Software programmers, Fresher, Business analysts , and Six sigma consultants can attend this course.
Yes, placement assistance is provided through various interview preparation sessions. The learner will undergo the training if he/she has completed the course.
Yes, value added courses are given as a part of the curriculum. The basic concepts in Python, R, MySQL, Hadoop, Artificial intelligence, Tableau and Spark are taught to the candidate.
The candidate can chat with the course guidance team or call them via 1800-212-2120 or chat on WhatsApp via +91 91082 38354
Yes, the freshers can find more jobs as business analysts. This course helps the candidate to gain conceptual knowledge in the business analytics domain that would help them to get better career opportunities.