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Certificate Program in DATA ANALYTICS

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Online Data Analytics Course
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Why Should You Learn Data Analytics?

High Demand & Jobs – Every industry needs data analysts.
High Salary – Earn ₹5-8 LPA+ in India.
Easy to Start – No coding required; learn in 2-4 months.
Used in Every Industry – IT, Finance, Healthcare, Marketing, etc.
Work in Top Companies – Google, Amazon, TCS, Infosys, etc.
Helps Business Growth – Make data-driven decisions.
Freelance & Remote Work – Earn ₹50,000+ per month.
Career Shift to Tech – Perfect for beginners & professionals.

Future-proof your career with Data Analytics!

 

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DATA ANALYTICS Course Syllabus

  • What is Data Analytics?

  • Types of Data Analytics (Descriptive, Diagnostic, Predictive, Prescriptive)

  • Applications of Data Analytics in Different Industries

  • Mean, Median, Mode, Standard Deviation, Variance

  • Probability & Distribution

  • Data Cleaning & Preprocessing

  • Handling Missing Data

  • Data Sorting & Filtering

  • Pivot Tables & Charts

  • Statistical Functions in Excel

  • Data Visualization in Excel

  • Introduction to Databases & SQL

  • CRUD Operations (Create, Read, Update, Delete)

  • Joins, Aggregations & Subqueries

  • Data Cleaning Using SQL

  • Introduction to Data Management
  • How do professionals organize their data?
  • Meta Data and Big Data
  • Freelance Data Entry Jobs
  • Introduction to Typing
  • Keyboarding
  • Ergonomic Typing

Using different types of keys and symbols in typing Google Docs – Voice Typing Lipikaar App

  • Using different types of keys and symbols in typing
  • Google Docs – Voice Typing
  • Lipikaar App
  • Text Formulas
  • Text Manipulation Functions
  • Apply Custom Data Formats
  • Use Advanced Fill Options
  • Apply Advanced Conditional Formatting and Filtering
  • Apply Custom Styles and Templates
  • Use Form Controls
  • Prepare Workbooks for Internationalization
  • Use Outlines
  • Use Custom Views
  • Basic Excel Charts
  • Use Area, Scatter & Stock Charts
  • Use Surface, Radar & Combination Charts
  • Create Custom Chart Templates
  • Work with Sparkline’s
  • Pivot Tables
  • Use Pivot Charts
  • Create Dashboard using Pivot Table
  • Using Power Query
  • Use of Macros
  • Using Data Tables
  • Create Dashboard using Pivot Table
  • Using Power Query
  • What is SQL?
  • Purpose of SQL
  •  What are the subsets of SQL? Data Definition Language
  • Data Manipulation Language
  • Data Control Language
  •  SQL vs. NoSQL
  • What is a Database?
  • Database Objects
  • Database Tables
  • Table Records
  • Types of Database Management Systems
  • Relational Database Management Systems
  •  SQL/Relational Databases vs. No SQL Databases
  • Download MS SQL Server or Oracle or MySQL Database Engine
  • Install. Launch SQL Server Management Studio
  • Select New Query
  • launch SQL Query
  • Type SQL Commands and Execute.
  • Focus on SQL Syntax
  • SQL keywords
  • SQL is not case sensitive
  • SQL Comments
  • SQL Commands
  • writing SQL Statements.
  • SQL Numeric data types
  • Date and Time data types
  • Character and String data types
  • Unicode character string data types
  • Binary data types
  •  Miscellaneous data types.
  • SQL Arithmetic Operators
  • Comparison Operators
  • Logical Operators
  • Bitwise Operators
  • Clauses in SQL are similar to conditionals in high-level languages. We have a large variety in the SQL clauses like the Where clause, Union Clase, Order By clause, etc.
  • The SQL Joins clause is used to combine records from two or more tables in a database. A JOIN is a means for combining fields from two tables by using values common to each.
  • Views in SQL are kind of virtual tables. A view also has rows and columns as they are in a real table in the database. We can create a view by selecting fields from one or more tables present in the database.
  • What is Python
  • Python history
  • Versions of Python
  • Features of Python
  • Limitations of Python
  • Scripting language vs programming language
  • Applications of Python
  • Python2 vs Python 3
  • What is Python used for?
  • Flavours of Python
  • Python compared to other languages
  • Python vs Java
  • How Python works? What is byte code and pycache?
  • What is PVM
  • Compiler vs interpreter
  • Compile time vs runtime
  • Future Scope of Python and career opportunity
  • What is Memory Management
  • Three areas of Memory Management
    • Memory management at Hardware level
    • Memory management at OS level
    • Memory management at Application level
  • How important is memory management
  • What is Memory management in Python
  • Python memory allocation – Static memory and Dynamic memory
  • 2 parts of memory – Stack and Heap
  • Garbage collector
  • Reference counting in Python
  • Transfering the garbage collector
  • Importance of Performing Manual Garbage Collection
  • Python Memory Management
  • Common Ways to Reduce the Space Complexity
  • Python Installation on windows
  • Check Python version on windows
  • Verify Python is installed?
  • Verify pip was installed?
  • What is IDLE and editors
  • How to run Python program using IDLE
  • How to install visual studio
  • Executing Python program
  • Identifiers and rules to write identifiers
  • Constants and variables
  • Keywords or reserved keywords
  • Python comments
  • Python syntax
  • Lines and Indentation
  • Python user input
  • Text type
  • Numeric types
  • Sequence type (range vs xrange)
  • Mapping types
  • Boolean types
  • Binary types
  • None type
  • Type casting
  • Arithmetic operators simulation
  • Assignment operators simulation
  • Comparison operators simulation
  • Logical operators
  • Identity operators simulation
  • Membership operators simulation
  • Bitwise operators simulation
  • Precedence and Associativity of Operators
  • Ternary operator
  • What are control flow statements in Python?
  • Decision control statements
  • Python conditions and indentation
    • simple if flow
    • if else flow
    • nested If flow
    • if elif else flow
    • elif ladder
    • short hand if, if else flow
  • Multiple conditions in if using and or operator
  • What other languages do? Which one is better?
  • Transfer statements
  • Break
  • Continue
  • Pass
  • Iterative statement
  • For
  • While
  • Pattern programs
  • Data types in brief
  • How to define string
  • How to access string and indexing
  • String slicing
  • Mutable and immutable
  • Mathematical Operators for string (+,*)
  • Comparison of string
  • String membership
  • Format string
  • Escape character
  • Removing spaces from string
  • Finding substring
  • Counting substring and len()
  • Replacing a string
  • Splitting and Joining of string
  • Changing case of a string
  • Checking starting and ending part of the string
  • Methods to check type of characters present in string
  • Revision string methods
  • What is list and its creation
  • Accessing elements of list
  • Mutability and immutability
  • List Traversing
  • Functions of list – get information about list
  • Manipulating list
  • Ordering elements of list
  • AIterative statement
  • Use of mathematical operators for list
  • Comparison and membership operators
  • Nested list
  • List comprehension
  • What is tuple and how to create tuple
  • Accessing tuple
  • Mathematical Operators for tuple
  • Functions of tuple
  • Tuple Packing unpacking
  • Tuple comprehension
  • Difference between list and tuple
  • SET and its creation
  • Important functions of set
  • Mathematical Operations on set
  • Membership operators
  • Set comprehension
  • Set won’t support slicing and indexing
  • Dictionary and its creation
  • Accessing dict data
  • Updating and deleting dict
  • Loop dictionaries
  • Important functions of dict
  • Dict comprehension and nested dictionaries
  • Functions and its types
  • Parameters
  • Return statement
  • Types of arguments part 1
  • Types of arguments part 2
  • Types of variable
  • Namespaces and Global keyword
  • Recursive function
  • Nested function
  • What is anonymous function
  • Difference between normal function and anonymous function
  • Lambda function in detail
  • Filter, map and reduce functions
  • Decorators
  • Calling decorators
  • Decorator chaining
  • Generators
  • Advantages of Generators
  • Generators vs Normal collections wrt performance
  • Generators vs Normal collections wrt performance
  • Iterators
  • What is Module
  • Module aliasing
  • Various possibilities of import
  • Reloading a module
  • Finding members of module by using dir()
  • The special variable name
  • What is package
  • init.py
  • What is library
  • Random module
  • Math module
  • Python Imaging Library (PIL)
    • MoviePy
    • pyscreenshot
  • What is Date Time module and its classes
  • Date class and its attributes
  • Date class methods
  • Time class and its attributes
  • Time class and its methods
  • DateTime class and its attributes
  • DateTime class and its methods
  • Timedelta class and its attributes
  • Timedelta class and its methods and operations supported
  • Tzinfo and timezone class
  • File handling basics and types of files
  • Opening a file with different modes and closing file
  • Various properties of file object
  • Writing data and reading data from text file
  • The with statement, sick(), tell()
  • OS module and working with directories
  • OS module functions
  • Running other programs from python program
  • Handling Binary data
  • Handling CSV file
  • Zipping unzipping files
  • What is Django?
  • Features, MVT Architecture vs MVC.
  • Creating and activating venv.
  • Installing Django
  • Django-admin startproject
  • Startapp, project structure
  • Urls.py
  • Path
  • Include
  • Connecting views to URLs
  • Function-based views (HttpResponse, render())
  • View logic

  • Introduction to Python & Jupyter Notebook

  • Libraries: Pandas, NumPy, Matplotlib, Seaborn

  • Data Manipulation & Visualization

  • Exploratory Data Analysis (EDA)

  • Power BI & Tableau Basics

  • Creating Dashboards

  • Interactive Visualizations

  • Supervised vs Unsupervised Learning

  • Regression & Classification Basics

  • Introduction to ML Libraries (Scikit-Learn, TensorFlow)

  • Real-World Data Analysis Project

  • Industry-Based Case Studies

  • Resume & Portfolio Building

  • Use What-If Analysis Tools
  • Create Scenarios
  • Merge Scenarios
  • Create Scenario Summaries
  • Use Data Tables
  • Manage Workbook Versions
  • Copy Styles between Workbooks
  • Copy Macros between Workbooks
  • Use Track Changes and Comments
  • Merge Workbooks
  • Protect Workbooks for Sharing
  • Connect To External Data
  • File Conversion from PDF to Word
  • Functions
  • Apply functions in formulas
  • Mathematical Functions
  • Financial functions
  • Useful Data Functions
  • Some Other Useful Functions
  • Look up data by using functions
  • Apply advanced date and time functions
  • Functions for Manipulating Text
  • Arrays
  • Working with Google Sheets
  • Working with Google Forms
  • Working with Google Keep
  • Using OpenOffice.org Writer
  • Using OpenOffice.org Calc
  • Using Komprehend
  • Using Google Data Studio
  • Using Komprehend
  • Excel Shortcuts
  • Mail Merge in MS Word
  • Compare Docs using MS Word
  • What is a DBMS and its purpose?
  • Types of DBMS
  • Examples of DBMS – MySQL, Oracle, etc.
  • SQL Boolean Expression
  • SQL Numeric Expression
  • SQL Date Expression
  • SQL Comments, Comments are used to explain sections of SQL statements
  • to prevent the execution of SQL statements. Single-Line Comments
  • Multi-line Comments
  • SQL Data Definition Language Commands
  • Create Alter
  • Drop Truncate and Rename Data Definition Language  Operations
  • Create a Database Use Database
  • Rename a Database
  • Drop Database
  • Create a Table Rename Table
  • Add a Column to exiting Table
  • Add multiple columns to existing Table
  • Modify an existing column, Rename a Column
  • Drop a Column
  • Truncate a Table
  • Drop a Table
  • Data Manipulation Language Operations
  • Retrieving data from a table
  • Inserting data into a table
  • Updating existing data into a table
  • Deleting all records from a table.
  • DCL includes commands such as GRANT and REVOKE which mainly deal with the rights
  • permissions
  • other controls of the database system.
  •  
  • SQL has many built-in functions for performing calculations on data
  • SQL Aggregate Functions
  • SQL String Function
  • SQL Date Functions SQL Scalar functions.
  •  
  • A Query is used to traverse over some data that may be of small or large quantity to find the needed information.
  • A Subquery is a type of query which is written inside another query. A subquery becomes a part of a larger query. A subquery is also called INNER QUERY OR NESTED QUERY.
  • An index is a schema object. It is used by the server to speed up the retrieval of rows by using a pointer. It can reduce disk I/O(input/output) by using a rapid path access method to locate data quickly.
  • SQL injection, also known as SQLI, is a common attack vector that uses malicious SQL code for backend database manipulation to access information that was not intended to be displayed. This information may include any number of items, including sensitive company data, user lists, or private customer details.
  • Types of errors
  • What is Exception
  • Pythons Exception handling hierarchy
  • Customized try except – with try except, without try except
  • Control flow in try except
  • Printing exception information
  • Try with multiple except blocks
  • Single except block can handle multiple exceptions
  • Default except block
  • Finally block
  • Control flow try except and finally
  • Nested try except finally
  • Else with try except finally
  • All possible combinations of try except finally
  • Types of exceptions
  • What is log and log file in programming
  • Logging the exception
  • Logging levels
  • BasicConfig and formatting
  • Python logging getlogger
  • File handler working with file handlers
  • Different logger object
  • Classes and functions
  • Capturing stack traces
  • What is JSON
  • JSON to Python and Python to JSON
  • Json dumps
  • Json loads
  • Serializing deserializing
  • Pickling unpickling
  • Need of pickling and unpickling
  •  
  • What is Reg ex
  • Character classes
  • Quantifiers
  • Important functions of re module
  • Symbols
  • Web scrapping using reg exp
  • Programs related to reg exp
  • Multi Threading and its types
  • Ways of creating thread in Python
  • Difference in program with – without multi threading
  • Thread identification number(ident)
  • Function/methods on multithreading
  • Daemon Threads
  • Synchronization
  • Difference between lock and semaphore
  • Inter thread communication
  • What is class
  • How to define class
  • What is object
  • Reference variable
  • Self
  • Constructor
  • Difference between constructor and methods
  • Types of variables – instance variable, static variable, local variable
  • Types of methods – instance method, setter getter method, class method, static method
  • Inner class
  • Garbage collectors
  • Garbage collection methods
  • Destructor
  • What is inheritance
  • Super class sub class
  • Benefits of inheritance
  • Creating child class
  • Types of inheritance – single inheritance, multilevel inheritance, multiple inheritance, hierarchical inheritance, hybrid inheritance
  • What is Polymorphism
  • How to use Polymorphism
  • Duck typing (philosophy)
  • Strong typing and hasattr() function
  • Overloading and its types
  • Operator overloading
  • Method Overloading
  • Constructor overloading
  • Method overriding
  • Constructor overriding
  •  
  • What is encapsulation
  • Why we need encapsulation
  • How to achieve encapsulation in Python
  • Access modifiers in encapsulation
  • Private members
  • Public method to access private members
  • Name Mangling to access private members
  • Protected members
  • Public members
  • Advantages of encapsulation
  • Data Abstraction in Python
  • Why abstraction is important
  • Abstraction classes in Python
  • Abstract base class ABC and its working
  • What is database
  • Python supports various databases
  • Why we are using MySQL
  • MySQL driver installation
  • Learn to write connector
  • Creating connection
  • Check connection
  • Close connection
  • Create database
  • Create table
  • Primary key
  • Foreign key
  • CRUD operation
  • Close connection
  • MySQL INSERT
  • Cursor Methods and Execute methods
  • MySQL select
  • Fetch methods, row properties rowcount,id
  • MySQL WHERE
  • Wildcard characters
  • MySQL ORDER BY
  • MySQL DELETE
  • Commit and rollback
  • MySQL drop table
  • MySQL UPDATE
  • MySQL LIMIT
  • MySQL JOIN
  • Parameterized query, Tuple parameter,dictionary parameter
  •  
  • What is GUI programming?
  • Methods while creating the Python application with GUI – TK, mainloop
  • Widgets in tkinter application – Button, Canvas, Checkbutton, Entry, Frame, Label, Listbox, Menubutton, Menu, Message, Radio button, Scale, Scrollbar, Text, Toplevel, Spinbox, Pannedwindow
  • What is the purpose of collection module
  • Counters
  • Ordered dict
  • Default dict
  • Chainmap
  • Namedtuple
  • DeQue
  • UserDict
  • UserList
  • UserString
  • Python fundamental Programs
  • Calculator
  • Password Generator
  • Tic Tac Toe
  • Rock Paper Scissors
  • Chat Bot
  • BMI Calculator
  • Story Generator
  • Quizz
  • Create Acronyms
  • Introduction to Django
  • Django Project and App life cycle
  • Creating Project and App
  • Django Templates and Static
  • Django Models
  • Django Forms
  • Django Views
  • Django Sessions and Cookies
  • Django Serialization,Deserialization and Mixins
  • Django Authentication and Authorization
  • Django Middleware
  • Send Email in Django and CSV,PDF files and GIT & Github
  • Django Rest Framework Introduction
  • Django Rest Framework Serializer and Deserializer
  • Django Rest Framework Views
  • Django Rest Framework Authentication And Authorization
  • Django Rest Framework Pagination and Routers
  • Learn basics of Artificial Intelligence with Python
  • Learn basics of Machine Learning with Python
  • Learn Data Science basics with Python
  • HTML
  • Django Template Language ({{ }}
  • Base.html inheritance
  • CSS/JS setup
  • Using {% static %} in templates
  • Defining models
  • Migrations
  • Using SQLite
  • Intro to
    Django Admin
  • Handling forms
  • Forms.ModelForm
  • Create/Read/Update/Delete data
  • Register
  • Login
  • Logout
  • Login_required
  • Showing user info in templates
Data Science Syllabus

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About Data Analysis

Data Analysis is the process of collecting, cleaning, processing, and interpreting data to find useful insights and support decision-making. It helps businesses understand trends, improve performance, and make data-driven decisions.

The process involves data collection, cleaning errors, analyzing patterns, and visualizing results using tools like Excel, SQL, Python, Power BI, and Tableau. Data analysis is widely used in business, marketing, finance, healthcare, and e-commerce to optimize strategies and improve efficiency.

With high demand and great career opportunities, learning data analysis can boost your career and help businesses grow! 

Enroll Now

Our Location Center

Anubhav Data Science Class Near Chembur Station (Head Office)

Anubhav Data Science Class Near Govandi Station

Anubhav Data Science Class Near Chembur Naka

Frequently asked questions For Data Analysis

Data Analysis is the process of collecting, cleaning, and interpreting data to find insights and make informed decisions.

Anyone! Students, working professionals, and business owners can learn it. No coding experience is required to start.

Popular tools include Python, R, SQL, TensorFlow, Scikit-Learn, Power BI, and Tableau for data analysis and machine learning.

Yes, a certificate is provided upon course completion, and placement assistance is offered to help you secure relevant job opportunities.

The course fee is 50,000/- for the entire program.

The course duration is 5 months, providing a condensed and intensive learning experience.

Data Analysis Course with Certification and
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This Data Analysis certification course will give you hands-on development experience and prepare you for an exciting career as a professional Data Science. Training Course will teach you the Data Science with the certification 100% guarantee placement.

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