Data Analytics Course ▷ Salary Upto 6 LPA ▷ SLA, Online

Python Data Analytics Training Course

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Data Analytics Training Course

Data Analytics Certification

Furnish the skills of fresher/Experienced at corporate by delivering industry admirable certification for Data Analytics training.

Experienced Faculty

Complete practical training by expert Sr. Lead Analyst/Technical Analyst With having 10+ Years of experience.

Placement Assistance

Placement assistance would be 100% after completion of 70% of Data Analytics training our dedicated placement team arrange interview till placement.

Lab Facility

Unfold your Advanced Excel skills with corporate level with technical test series with Practical Training to furnish aptitude

Data Analytics Workshop

Experience unique and lively – Real time projects learning and case study for learners at SLA’s workshop.

Admin Support

Complete assistance for fresh batch schedule/re-scheduling classes/arrange doubt classes to the Learners.

Data Analytics Course

What is the correct answer for 26 + 16

Data Analytics Programme Modules

Data Analytics Training Course

Module 1 - Basic and Advanced Excel With Dashboard and Excel Analytics

Introduction to Excel:-
- Basic Understanding Menu and Toolbar, Introduction to different category of functions like Basics, Mathematical and Statistical, Date and Time, Logical, Lookup and References, Text and Information.
Mathematical Functions:-
- Sum, Sumif, Sumifs, Count, Counta, Countblank, Countif, Countifs, Average, Averagea, Averageif, Averageifs, Subtotal
- Aggregate, Rand, Randbetween, Roundup, Rounddown, Round, Sumproduct
Date and Time Function:-
- Date, Day, Month, Year, Edate, Eomonth, Networkdays, Workday, Weeknum, Weekday, Hour, Minute, Second, Now, Today, Time
Text Functions & Data Validation:-
- Char, Clean, Code, Concatenate, Find, Search, Substitute, Replace, Len, Right, Left, Mid, Lower, Upper, Proper, Text, Trim, Value, Large, Small Filters (Basic, Advanced, Conditional), Sort (Ascending, Descending, Cell/ Font Color), Conditional Formatting, Data Validation, Group & Ungroup, Data split.
Statistical Function & Other Functions:-
- Isna, Isblank, Iserr, Iseven, Isodd, Islogical, Isytext, Max, Min, Len, Right, Left, Mid, ,Maxa, Maxifs, Median, Minifs, Mina, Vara, Correl, Geomen
Logical Functions:-
- And, Or, If, Iferror, Not, Nested If
Lookup & Reference Functions:-
- VLookup, HLookup, Index, Match, Offset, Indirect, Address, Column, Columns, Row, Rows, Choose, Arrays Concept In Lookup Formula’s, Past Special, Past link
Pivot Table – MIS, Data Analysis & Visualization:-
- Pivot Table- What-if Analysis, Data Table –One Variable and Two Variables, Data Analysis Using Statistics, Descriptive Statistics, ANOVA, Moving Average, Testing Hypothesis, Measuring Covariance and Correlation, Distribution, Regression, Graphs & Charts, Analysis Tool Pack, Solver, Histogram, Pareto, Water Fall, Import and Export data, Protect/Unprotect sheets/workbooks, Worksheet formatting and Print Display
Data Collection Method:-
- With Data Quality, Collaboration & Security Like Share Your Workbook On Share Drive With Quality
Analysis Single/Multidimensional Analysis:-
- Like Three Dimensional (3D) Tables, Sensitive Analysis Like Data Table, Manual What-If Analysis, Threshold Values, Goal Seek, One-Variable Data Table, Two-Variable Data Table
Advanced Dashboard in Excel:-
- Overview of Chart types, Chart Formatting, Active X Form Controls, Principle of great dashboard design, Selecting Correct Chart to display data, Interactive Charts with Form Controls, Combo box, Check Box, Scroll Bar and Radio Button, Interactive Dashboard with Form Controls, Form Controls for reports automation, Data Models using Power Pivot
Two Live Report Development in Advanced Excel:-(Real World Data):-

Module 2 - VBA / Macros - Automation Reporting, User Form and Dashboard

Dashboard Reports Allow User to Get High-Level Overview of the Business and Help Them Make Quick Decisions. Dashboards are Often Called as Management Information System (MIS), Which Provides Information that Organizations Require to Manage Themselves Efficiently and Effectively.

To Define KPIs (Key performance Indicator), Customer Service Dashboards or Project Management Dashboard (Gantt Chart)
Dashboard Reports Based on Tables and Number or Charts/Graphs or Both.
Introduction to Programming Introduction to logical thinking flowcharts & algorithms:-
Define Objective, Start & End Points; Identifying Solution & Breaking it Into Sequential Steps Writing a Algorithm:-
Step-by-Step Instructions, Flowcharts, Process Flow Diagrams. Excel Macros – an Introduction:-
Complete Review of the VBA Language (Subs, Functions, Variables, Arrays, Loops, Logic…etc.):-
- Excel Macro Language Review (VBA) Including Variables, Data Types, Constants, Arrays, Operators, Expressions, Loops, Logic Decisions And Calling
- Overview Of Commanding Excel Using VBA Including A Discussion Of Objects, Properties And Methods
- The Power of Macros – What, When, How to use Macros.
- Introduction to Object Oriented Programming
- Objects, Its Functions, Methods and Properties Introduction to Events
- Details of Events, How & When to use of Events, Preparing to ‘Macro’ Visual Basic Editor (VBE) – Developer Tab, Security
- Introduction to the VBE, Properties window, Project Explorer, Password Protection of Code How to use the VBE – Features, Options, Intelligence Technology
- Debugging Mode, Bookmarks, Breakpoints, Watch Window, Immediate Window and Locals Window Inbuilt VBE Help Feature – Tips and Tricks
- Form Controls vs. ActiveX Controls Getting into the Code
- Message Box and Input Box Working with Data in Excel through VBA
- Data Types, Constants and Variables
- Different type of data type; How and When to use Variables to Store Information.
- For-Next, For-Each, Do-While, Do until, Do Loop Decision-Making and Code Branching
- If-Then-Else, Select-Case, And/or Nested Conditions
- What is user’s Defined Functions?
- How to create & use them.
- Use of Arrays in VBA programming with one dimensional, two dimensional or multi-dimensional analysis
Excel VBA Power Programming For VBA Macros:-
- Working with Dynamic Ranges. Protecting Worksheets, Cells and Ranges. Working with Multiple Files. Opening & Saving Files
- How to Analyze Data On Multi Worksheets And Build Summary Sheets
- How to Access The Windows File And Folder System To Open And Close Workbooks
- How to Protect Your Code Against Errors
- How to Use Excel And VBA To Create Basic Dash Boards
- How to Create Your Own Custom Business Worksheet Functions In VBA
- How to Create Basic Report Generation Tools Using Excel VBA, Microsoft Word And PowerPoint
- How to Use The Excel Visual Basic Macro Recorder To Record Excel Tasks In VBA And Then Interpret The Code
Overview of Using User forms To Create Business Wizards:-
- Working with User Forms & User Forms Events like List box, Combo box, Option Buttons, Check box, Text box, Labels, Command button, Toggle button./li>
- How to create dynamic dashboard on user form with different controls/li>
- How to link various user form with each other to create a complete interface between user and system/li>
Connection between Excel VBA & other platforms:-
- How to Establish Connection Between VBA and Internet Explorer to Open any Internet Website through VBA
- How to Establish Connection Between Excel VBA and power presentation to create power point through VBA
- How to Establish Connection Between Excel VBA and Access database to update the data in access through VBA
- How to Establish Connection Between Excel VBA and outlooks through VBA
- How to Establish Connection Between Excel VBA and MS Word through VBA
Testing and Debugging Your Code:-
- Types of Errors
- Using Breakpoints
- Debugging Techniques
- Dialogue Boxes
- UsingMsgBox Function
- UsingInputBox Function
- Working with FileDialog
- Working GetOpenFilname Method
- Working GetSaveAsFilename Method
Effective Error Handling:-
Automation Development Reports & Live Projects:-

Module 3 - SQL and MS Access - Data Manipulation, Queries, Scripts and Server Connection - MIS and Data Analytics

MS Access is a relational database management system (RDBMS) from Microsoft that combines the relational Microsoft Jet Database Engine with a graphical user interface and software-development tools. … It can also import or link directly to data stored in other applications and databases.

Introduction to SQL:-
- SQL Course overview
- Installing the test environment
- What is SQL?
- Editors and Platforms to learn SQL
Complete SQL in a Class:-
- Quick-start introduction
- Using the basic SELECT statement
- Selecting rows
- Selecting columns
- Counting rows
- Inserting data
- Updating data
- Deleting data
- Import and Export data
Fundamentals of SQL:-
- Databases and tables
- SQL syntax overview
- Data Definition, Data Manipulation, Data Control, Transactional Control statements
- Creating tables
- Deleting a table
- Inserting rows into a table
- Deleting rows from a table
- What is NULL?
- Controlling column behaviors with constraints
- Changing a schema with ALTER
- Filtering data with WHERE, LIKE, and IN
- Removing duplicates with SELECT DISTINCT
- Sorting with ORDER BY
How Relationships Work in SQL:-
- Understanding joins
- Accessing related tables with JOIN
- Multiple related tables

Explaining SQL Strings:-
- About SQL strings
- Finding the length of a string
- Selecting part of a string
- Removing spaces with TRIM
- Making strings uppercase and lowercase
Numbers and SQL:-
- About numeric types
- Finding the type of a value
- Integer division and remainders
- Rounding numbers
SQL Functions and Clause:-
- The Aggregate functions MIN, MAX, AVG, SUM and COUNT, UPPER, LENGTH, LOWER
- The GROUP BY and HAVING clauses Grouping in a combination with joining
Triggers in SQL:-
- Concept of Trigger
- Create Trigger for (Insert,Update,Delete)
- Alter Trigger
What are Subselects and Views in SQL:-
- Creating a simple subselect
- Searching within a result set
- Creating a view
- Creating a joined view
Maintaining SQL Server Database:-
- Backup Database
- Restore Database
SQL Server Job Creation:-
- How to create job in SQL Server Agent
- How to schedule job

Topics Covered as follows: Access

Access environment and tools
Database terminology and concept
Designing database in Access
- Join Tables That Have No Common Fields
- Work with Subdatasheets
- Create Sub queries
Working with the runtime of Tables
Data migration and importing
Working with the Design side of Queries
Working with the runtime of Queries
Working with the Design side of Forms
- Adding Controls to Forms
- Creating Sub forms
- Organizing Information with Tab Pages
- Displaying a Summary of Data in a Form
- Applying Conditional Formatting
Working with the runtime of Forms, Managing Switchboard

Understanding RDBMS
Working with the Design side of Tables
- Create Query
Working with the Design side of Reports
- Organize Report Information
- Format Reports Include Charts in a Report
- Add a Calculated Field to a Report
- Add a Sub report to an Existing Report
Working with the runtime of Reports
Working with the Design side of Macros
- Creating a Macro Restricting Records Using a Condition
- Automating Data Entry Using a Macro
Working with the runtime of Macros
How to create a functional specification
Build a real-world business application
Putting altogether and deployment

Module 4 - Tableau | MS Power BI ▷ BI & Data Visualization

Module 4 a) Tableau
Module 1 – Getting Started with Tableau
- Overview Of Tableau
- Tableau Architecture
- Installation And Configuration Of Tableau 10
Module 2 – Connecting to The Data
- Managing Metadata
- Managing Extracts
- Data Sources
- Cross-Database Joins
- Data Aggregation And Data Ports
- Tableau Charts
- Bar Charts and Stacked Bars Data Blending
- Tree Maps and Scatter Plots
- Individual Axes, Blended Axes, Dual Axes and Combinational Chart
Module 3 – Visual Analytics
- Drill Down and Hierarchies
- Sorting, Filtering and Grouping
- Trend and Reference Lines
- Forecasting and Clustering
- Analysis with Cubes and MDX
Module 4 – Developing First Bar Char
- Connecting Tableau to Data File
- Navigating Tableau
- Calculated Fields
- Adding Colors, Labels and Formatting
Module 4 b) MS Power BI
A Quick Introduction
- What is MSPBI and its scope
- Learn the common work flow in MSPBI
- Building blocks of MSPBI and its relations
- Quick demo how to create a business dashboard in MSPBI
- MSPBI components
- Old vs. new technologies
- Power BI Desktop/Service/Mobile
Getting Business Data
- Get data in shape for use with MSPBI
- Combining two or more data sets (source data) for reporting
- Tackling messy data in MSPBI
- Clean and transform data
Modelling in Power BI
- How to connect many different data sources
- Manage data source (database) relationships
- Unique keys
- Calculated columns and more
- Custom calculations to evaluate time-based functions
- Build calculated tables based on DAX formulas and expressions
- Creating and viewing visuals easier with optimized models
- Discover hierarchal drill-down tools for date fields
Data Visualization
- Create and customize visualization in MSPBI and its power
- Use combination charts

Module 5 – Time Series, Maps and Aggregation
- Data Extracts and Time Series
- Understanding Granularity, Aggregation and Level of Details
- Default Location in Maps
- Custom Geo Coding
- Symbol Map and Filled Map
Module 6 – First Dashboard
- Into Section
- Joining Data In Tableau
- Working With Maps and Hierarchies
- Scatter Plot and Applying Filters in Different Sheets
- Creating First Dashboard
Module 7 – Blending Data and Dual Axis Charts
- Duplicate Values
- Multiple Fields
- Data Blending
- Dual Axis Chart
- Building Calculated Fields
Module 8 – Table Calculation and Storytelling
- Downloading Dataset and Connection
- Mapping
- Building Table Calculation For Gender
- Bins and Distributions for Age
- Tree Map Chart
- Advanced Dashboard
- Storyline and Storytelling
Module 9 – Data Preparation
- Data Format
- Data Interpreter
- Multiple Columns And Pivot
- Metadata Grid
- Advanced Data Preparation
- Create and format slicers with it
- Map visualizations and its utilization
- Use tables and matrixes
- Long live bubbles
- scatter charts in action
- Advanced funnel and waterfall charts
- Drive fast dashboard insights with gauges and numbers
- Color your visualization world with colors
- shapes and scales
- Adding personal touch
- logo etc. to reports and dashboards
- Display and present your dashboard in a way you want with summarize data
- Control how your report elements overlap with each other
- Learn to drill into hierarchies
- Manage how levels are shared (Z-order in reports)
- How to use R visuals in MSPBI
Data Exploring & Sharing
- Quick insights in Power BI Service
- Create and configure a dashboard
- Share dashboard with your organization
- Display and edit visuals- tiles
- full screen
- Get more space on your dashboard
- Install and configure a personal gateway
- Excel and MSPBI
- Import and excel table into Power BI
- Import excel files with data models and power view sheets
- Connect One Drive for business to MSPBI
- Excel data in Power BI summary
DAX (Data Analysis Expression) Application
- DAX and its basic building blocks
- Create calculated columns (fields) and measures in MSPBI using DAX formulas
- Breadth of functions available in DAX
- User variables in DAX
- Create expressions across multiple tables with relational functions;
- Filter and evaluate tables using advanced table functions

Module 5 - Python | R Programing ▷ BI & Data Visualization

Module 5 a) R-Programming
Module 1- Introduction to Business Analytics
- Introduction to Business Analytics
- Types of Analytics
- Case study on Walmart, Signet Bank
- Data Science and its importance
Module 2- Introduction to R
- Introduction to R
- Installing R
- Installing R Studio
- Workspace Setup
- R Packages
Module 3- R Programming
- R Programming
- if statements
- for statements
- while statements
- repeat statements
- break and next statements
- switch statement
- scan statement
- Executing the commands in a File
Module 4 – R Data Structure
- Data structures
- Vector
- Matrix
- Array
- Data frame
- List
- Factors
Module 5 – Apply Functions
- DPLYR & apply Function
- Import Data File
- DPLYP – Selection
- DPLYP – Filter
- DPLYP – Arrange
- DPLYP – Mutate
- DPLYP – Summarize
Module 6 – Apply Functions
- Data visualization in R
- Bar chart, Dot plot
- Scatter plot, Pie chart
- Histogram and Box plot
- Heat Maps
- World Cloud

Module 5 b) Python
Module 1 – Introduction to Python
- Python Overview
- Advantages and Disadvantages
- Installation and Configuration
- Interpreted Languages
Module 2 – Programming with Python
- Python Script
- Standalone Scripts Under Unix And Windows
- Using Variables and Operators
- Command Line Parameters
- Understanding Expressions
Module 3 – Flow Control
- If And Else If Statement
- The While and Loop Statement
- Continue Statement
- Break Statement
- Range () Function
- Using Lists
Module 4 – Sequence Data
- List Operations and Methods
- Sets
- Dictionaries
- Tuples
- Strings
Module 5 – Functions
- Defining Functions
- Parameters and Variables
- Using Global Statement
- Keyword Arguments
- Keyword Only Parameters
- The Return Statement
- Varargs Parameters
- Docstrings
Module 6 – Errors and Exception Handling
- Dealing Syntax Errors
- Exception Handling
- Cleaning Up
Module 7 – Modules
- Creating Modules
- The From and Import Statement

Module 7 – Apply Functions
- Introduction to statistics
- Type of Data
- Distance Measures (Similarity, dissimilarity, correlation)
- Euclidean space.
- Manhattan
- Minkowski
- Cosine similarity
- Mahalanobis distance
- Pearson’s correlation coefficient
- Probability Distributions
Module 8 – Hypothesis Testing I
- Hypothesis Testing
- Introduction
- Hypothesis Testing – T Test, Anova
Module 9 – Hypothesis Testing II
- Hypothesis Testing about population
- Chi Square Test
- F distribution and F ratio
Module 10 – Regression Analysis
- Regression
- Linear Regression Models
- Non Linear Regression Models
Module 11 – Classification
- Classification
- Decision Tree
- Logistic Regression
- Bayesian
- Support Vector Machines
Module 12 – Clustering
- Clustering
- K-means Clustering and Case Study
- DBSCAN Clustering and Case study
- Hierarchical Clustering
Module 13 – Association
- Association
- Apriori Algorithm
- Candidate Generation
- Visualization on Associated Rules
- Summary

Package
Dir Function
Module Name

Module 8 – Importing and Exporting Data
- Importing Data From Different Sources
- Connecting To Databse
- Viewing Data Objects And Sets
- Exporting Data To Other Formats
Module 9 – Data Manipulation and Data Analysis
- Cleansing Data With Python
- Data Manipulation
- Python Tools And In-Built Functions
- Formatting And Normalizing Data
- User Defined Functions
- Data Analysis Using Statistics And Graphical Representation
Module 10 – Data Structures and Regular Expressions
- List, Tuples, Dictionaries And Set
- Re Objects
- Pattern Matching
- Subexpressions
- Parsing Data
- Complex Substitutions
Module 11 – Live Practice Sessions
- Projects and Assignments
- Live Training

Module 6 - Python Data Science and Machine Learning - 100% Free in Offer - by IIT/NIT Alumni Trainer

Module 6.1

Introduction to Python Programming for Data Analysis:-
- Data types : int, float, str etc
- Operations on data types
- Data structures: list, dict, tuples, set
- Iterators/iterables
- functions

Pandas Dataframe, NumPy arrays
Data manipulation in pandas: slicing, subset, cross tabulation, aggregation

Reference Data for running example:-
- XYZ Company Dataset
- Titanic

Module 6.2

Data Exploration
- Univariate Statistics: mean, median, std.
- Bivariate Statistics : correlation , covariance
- Plots using Matplotlib,seaborn
- Concepts of inferential statistics
- Standardization
- log transform
- dummy variable creation

Dimensionality Reduction + Linear Transformation
- PCA
- LDA
- Matrix
- Determinant
- Matrix multiplication
- Element wise operations

Module 6.3

Supervised Learning
- Linear classifier: logistic regression
- Linear classifier: Support Vector Classifier
- Tree Classifier: Decision Trees
- Ensemble Classifier: RF, Boosted Trees
- Cost Function minimization
- Scikit learn library
- Regression

Machine Learning Concepts
- Bias , Variance
- Regularization
- Hyperparameter tuning
- Parametric / non parametric methods
- cross validation
- Sampling data

Module 6.4

Advanced Unsupervised Learning
- K means Clustering
- t- SNE
- Agglomerative Clustering

Module 6.5

Introduction to Text processing
- Tokenization
- N-grams
- TF-IDF
- cosine similarity
- Text Classification
- Topic Modelling
- spaCy library

Module 6.6

Introduction to Deep Learning
- Understanding a perceptron
- Forward propagation
- Backward propagation
- Parameter update
- CNN
- RNN: GRU, LSTM
- Regularization: dropout, data augmentation
- Optimization: Momentum, Adam, AdamW

Data loading
gradient descent
Framework
- PyTorch

Find the Data Analytics course details below.

Duration of Module

Data Analytics Course Module	Data Analytics Course Duration
Module 1-5 – Data Analytics	150 (Hours)

Batch Timings

MIS Analyst Course Schedule	MIS Analyst Timing
Monday to Friday	8:00 AM – 10:00 AM
Monday to Friday	10:00 AM – 12:00 PM
Monday to Friday	2:00 PM – 4:00 PM
Monday to Friday	4:00 PM – 6:00 PM
Saturday/Sunday	8:00 \| 12:00 \| 2:00 \| 4:00
Sunday	8:00 AM – 10:00 AM
Sunday	10:00 AM – 12:00 PM
Sunday	2:00 PM – 4:00 PM
Sunday	4:00 PM – 6:00 PM

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