Best Data Analytics Course Online


Ecare Upskill's online Data Analytics course is your key to becoming a proficient data analyst. Dive into data manipulation, visualization, and analysis techniques using industry-standard tools. Elevate your career prospects with hands-on projects and a curriculum designed to meet the demands of the data-driven world

Price ₹6,000 ₹999

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Data Analytics Training-Course Online

2 weeks

Live sessions


No Pre-recorded lecture

Course Content

  • What is a programming language?
  • Python interpreter
  • Python versions
  • Advantages of Python language
  • Uses & applications of Python in different domains
  • Installation of Anaconda
  • Different ways to run Python code
  • Write your first Python program
  • Multiline Print Statement and Comments in Python
  • Variables
  • Data Types
  • User-Input
  • Operators
  • Introduction to Conditional statement
  • Types
  • Types of Loops
  • For Loop
  • While Loop
  • Loops with a conditional statement
  • Infinite Loop
  • Nested Loop
  • Break and continue statement
  • Introduction to strings in Python
  • Indexing
  • Slicing
  • Iteration
  • String functions
  • Introduction to lists
  • Iteration
  • Slicing
  • List Functions
  • Introduction to sets
  • Iterations
  • Set methods
  • Introduction to tuples
  • Iterations
  • Function
  • Making tuples mutable
  • Creation of Dictionaries
  • Iterations
  • Dictionary Functions
  • Nested Dictionaries
  • Introduction
  • Types
  • Parameters
  • Arguments
  • Args Kwags Recursion
  • 3 Projects on Python
  • Introduction to Jupyter Notebook
  • Installing Jupyter Notebook
  • How to use Jupyter Notebook?
  • Introduction to Pandas
  • Installing Pandas
  • Pandas Series
  • Coding: Pandas Series
  • Pandas DataFrames- Working with Rows and Columns
  • Pandas DataFrames: Filtering Data
  • Coding: Filtering Data
  • Reading and Analysing CSV Files with Pandas
  • Coding: Reading and Analysing CSV Files
  • Reading Excel Files: GroupBy and Other Useful Operations
  • Working with Missing Data
  • Coding: Working with Missing Data
  • Test Your Knowledge: Pandas
  • Introduction to NumPy
  • 1-D Array
  • 2-D Array
  • Indexing
  • Slicing
  • Concatenating
  • Broadcasting
  • Statistical functions
  • Arithmetic functions
  • Introduction to Python Visualization Libraries
  • Installing Plotly
  • Creating Scatter Plots
  • Creating Line Charts
  • Line Charts
  • Creating Basic Bar Charts
  • Creating Grouped and Stacked Bar Charts
  • Creating Pie Charts
  • Pie Charts
  • Creating Histograms
  • Introduction to Python Visualization Libraries
  • Installing Plotly
  • Creating Scatter Plots
  • Creating Line Charts
  • Line Charts
  • Introduction to Power BI
  • Power BI Dashboard
  • Connectors
  • Basic Transformations in Power BI
  • Format Tool
  • Dealing with text tools
  • Dealing with Numerical Tools
  • Create a Table Using Power BI
  • Dealing with Date and Time
  • Pivoting and Unpivoting of data
  • Adding Conditional Columns
  • Merge queries and Append queries
  • Data model and importance of Data Modeling
  • Manage Data Relationships
  • Editing a Relationship
  • Cardinality and Cross-Filter Direction
  • Introduction to DAX
  • Importance of DAX in Power BI
  • DAX Expressions
  • Steps to Create Calculated Columns in DAX
  • Creation of Measures in Power BI and its types
  • Understanding DAX syntax in Power BI
  • DAX Functions in Power BI
  • Date and Time Functions
  • Text Functions Using DAX
  • Logical Functions Using DAX
  • DAX Operators
  • Introduction to Visuals in Power BI
  • Visualisation charts in Power BI
  • Filtering Options
  • Exploring Matrix Visuals
  • Filtering Data with Slicers
  • Number Cards and Text Cards
  • KPI Visuals
  • Modifying Colours in Charts And Visuals
  • Visualizing Data with Maps
  • Tree Map
  • Bookmarks and Buttons
  • Custom Power
  • Designing for Phone vs Desktop Report Viewers
  • Introduction to AI visuals
  • Working with AI visuals
  • Analyse data with AI visuals
  • Introduction to SQL
  • Installation
  • Datatypes in MySQL
  • Creation of a Database
  • Tables
  • Insert query
  • Select Query
  • Delete query
  • Update query
  • Joins in Database
  • Functions in Database
  • Advance concepts in DataBase
  • Introduction to MS Excel
  • Basic Functions of Excel
  • Sorting Data
  • Filtering Data
  • Basics of Formula/Functions
  • If Functions and text Functions
  • Date & Time Formula
  • Lookup and Information Functions
  • Using Conditional Formatting
  • Macros
  • Summarising Data with Pivot Tables
  • Working with Slicerss
  • Power Pivot / Power Query
  • Charts
  • Excel For Data Analytics
  • Data Visualization with Excel
  • Excel Dashboard
Critical thinking and problem-solving Data cleaning and preprocessing Data mining Data modeling Data visualization Machine learning Predictive analytics Programming languages and tools Statistical analysis

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Frequently Asked Questions

Data analysis is the process of examining, cleaning, transforming, and interpreting data to extract valuable insights, make informed decisions, identify trends, and solve problems. It is essential in various fields, such as business, science, healthcare, and social research, as it helps organizations and individuals better understand their data and make data-driven decisions.

No, prior data analysis experience is not always required. Ecare Upskill's online data analysis courses are designed for beginners and cover the basics of data analysis.

Online data analysis courses typically cover a range of topics, including data collection, data cleaning, statistical analysis, data visualization, hypothesis testing, and data interpretation.

Our online data analysis courses provide support through discussion forums and chat, where you can ask questions and seek assistance. Instructors or mentors are available to provide guidance, and peer interaction is encouraged for collaborative problem-solving.

Our online data analysis courses offer certificates of completion. These certificates can validate your skills and knowledge in data analysis and valuable for job applications and career advancement.

Progress in online data analysis courses is typically assessed through quizzes, assignments and practical data analysis exercises.

The software or tools used in data analysis courses include programming languages like Python, along with data analysis libraries and software such as Excel, Tableau, or specialized data analysis tools.

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