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Quick Facts

Medium Of InstructionsMode Of LearningMode Of Delivery
EnglishSelf Study, Virtual Classroom, Campus Based/Physical ClassroomVideo and Text Based

Course Overview

This course on Analytics / Data Analytics Certification Training Course in Delhi is a diploma from SGIT, Steinbeis University, Germany. It focuses on data science and teaches various theories related to it using case studies and capstone projects. The syllabus is designed by world class faculty at Steinbeis.

Data analytics is a process to analyze data quantitatively and qualitatively to deduce logical reasons and gather information at one place using machine learning and artificial learning. It is a new way and has a huge scope as every IT sector is now involving data analytics and are demanding data analysts. Students in this course will learn about extraction, data collection, transformation, cleansing, and exploration, statistical analysis, programming languages like R and Python.

After doing this course a candidate will get the status of an alumnus in Steinbeis. They provide placements in companies like Accenture and Infosys. They have a detailed curriculum which covers topics from basics to advanced and a personal mentor and they offer interview preparation sessions as well.

The Highlights

  • Status of alumnus in Steinbeis
  • Digital certificate
  • Live virtual classroom
  • Certification by EXCELR
  • In association with Steinbeis University, Germany
  • Course duration of 6 months
  • Dual certificate from ExcelR and Steinbeis Akademie

Programme Offerings

  • Live Session
  • videos
  • assignments
  • Projects
  • Recorded live sessions

Courses and Certificate Fees

Certificate AvailabilityCertificate Providing Authority
yesSteinbeis University, Berlin
Analytics Data Analytics Certification Training Course in Delhi Fees Structure :
CourseFees
Without IITM Pravartak Certification
₹ 44999 
With IITM Pravartak Certification
₹ 75999

Eligibility Criteria

Certification qualifying details 

A candidate shall be awarded with the certificate post completion of the course. To obtain this certificate candidate is required to take an online examination offered by them and should score 60% or more. After this the candidates can also check their alumnus status.

What you will learn

Data science knowledgeKnowledge of Data mining

The candidate will be able to learn the following things after finishing this course:

  • A candidate will be able to gain deep knowledge on concepts like regression modelling, hypothesis testing, predictive analytics and many more.
  • Students will be able to learn machine learning and apply in real life.
  • Candidate will be introduced to types of analytics.
  • Students will be able to learn association rules and develop a decision tree.
  • Candidates will be able to seek information about value-added courses like artificial intelligence, basics of MySQL, R, python and many other similar concepts.
  • Candidates will develop a hold on the recommender system.
  • They will learn end-to-end project description with deployment.
  • Participants will learn regularization techniques.

Who it is for

Following people can enrol for this course:

  • Business analysts are welcome to take this course.
  • Professionals who are willing to pursue their career in this field.
  • Digital marketing professionals are invited to this course.
  • Software programmers can take up this course.
  • Freshers who are serious to develop their career in this field.
  • Six Sigma consultants who are interested in this field.
  • People who are already employed in business intelligence tools, reporting tools and sectors of data warehousing.
  • Freshers from any stream who have good analytical and logical skills.

Admission Details

The course takers can follow the procedure given below to get enrolled successfully:

Step 1: Open the webpage of the course with the help of this link:  https://www.excelr.com/data-analytics-certification-training-course-in-delhi

Step 2: Choose the course you want to enrol in, live virtual classroom or self-paced.

If you choose to live virtual classroom,

Step 3: Click on enrol now. 

Step 4: Choose the time slot you are comfortable in.

Step 5: Enter your details.

Step 6: Make the payment.

If you choose self-paced course,

Step 7: Select the buy now option. 

Step 8: Enter your details as asked by them.

Step 9: Secure your payment details.

Step 10: Make the payment.

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
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 B
  • 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 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

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