NIIT India

Exploratory Data Analysis Using Python

Fees: ₹ 99,000 + 18% GST 380 hours
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NIIT empowers you to launch your career in Data Analytics
  • Expert-led learning – learn from top industry experts
  • Leverages GenAI tools to accelerate analytics efficiency
  • Build job-ready analytics skills through hands-on learning
  • Empower learners for careers in data analytics
  • Solve challenging real-world business problems efficiently with data analytics
  • Demonstrate end-to-end skills through a real-world capstone project
NIIT's placement assistance helps to kickstart your career
  • 100%Eligible learners placed*
  • ₹ 9 LPAKickstart your career with salaries up to*
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The NIIT advantage

Skills you gain

  • Design optimized databases and write efficient SQL queries
  • Visualize data to communicate insights and trends
  • Process and organize data to support analytics workflows
  • Master essential Excel skills for data analysis and reporting
  • Apply Python for data manipulation and insights
  • Build interactive dashboards for actionable insights
  • Enhance decision-making with AI-powered analytics
  • Apply hypothesis testing and regression techniques

What you’ll learn

    Data Analytics and Storytelling using Excel
  • Explore data categories & essential Excel functions
  • Streamline data import and cleanup
  • Analyze and summarize data with PivotTables
  • Visualize data with charts - I
  • Visualize data with charts - II
  • Measure central tendency of data
  • Handle outliers in the dataset
  • Explore and visualize spread and correlation in data
  • Combine data, visuals, narration to tell a story
  • Create visual summaries to enhance storytelling
    Data Analytics and Managing Data using SQL
  • Write basic SQL select queries
  • Combine data with joins
  • Summarize and organize data with queries
  • Retrieve data with subqueries
  • Modify and manage data using DML commands
  • Design databases using ER diagrams
  • Define database schemas with DDL
  • Ensure database consistency
  • Automate database operations
  • Explore JSON and NoSQL
    Data Analytics and Automation using Python
  • Write your first Python program
  • Make decisions with conditional statements
  • Implement iterative programming using loop statements
  • Implement modular programming using functions
  • Manipulate data with strings and lists
  • Organize data with tuples, sets, and dictionaries
  • Build programs using classes and objects
  • Handle errors gracefully and manage files
  • Manipulate data efficiently with NumPy and analyze with Pandas
  • Build AI-powered applications with Python and LLMs (API connect to LLMs)
    Exploratory Data Analysis with Python and GenAI
  • Prepare structured data for analysis using NumPy and Pandas
  • Combine, clean, and summarize DataFrames for analysis
  • Manage DataFrames using CRUD operations
  • Analyze and visualize data using Matplotlib and Seaborn
  • Perform descriptive statistical analysis using Python
  • Extract and analyze data from SQL using Python
  • Explore data patterns and trends – EDA Part I
  • Uncover insights using advanced techniques – EDA Part II
  • Accelerate EDA with GenAI tools in Python – Part I
  • Generate deeper insights with GenAI-assisted EDA – Part II
    Advanced Data Visualization and BI with Power BI
  • Extract and transform data for analysis
  • Prepare and structure data for efficient modeling
  • Design and implement effective data models
  • Optimize data models for performance and scalability
  • Apply DAX to perform calculations and data analysis
  • Implement advanced DAX for business insights
  • Develop impactful visualizations for data storytelling - Part I
  • Develop impactful visualizations for data storytelling - Part II
  • Design interactive and custom reports for users
  • Automate insights with AI-powered analytics
    Applied Statistical Analysis for Data Insights
  • Apply probability concepts to solve real-world problems
  • Apply sampling methods and analyze normal distribution
  • Perform Z and T-tests to do hypothesis testing
  • Prepare data for machine learning
  • Perform linear regression analysis
    Applied Data Analytics – Capstone
  • Data cleaning and preparation
  • Data visualization and EDA using Python, SQL, and Power BI
  • Dashboards in Power BI
  • Apply inferential statistics and regression analysis
  • Presentation and viva-voce

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Am I eligible to apply?

Unlock exciting career opportunities!
  • If you have a minimum of 50% in class X, XII, and graduation, you're eligible to apply.
  • Undergraduates must maintain at least 50% marks until the final year and achieve a minimum 50% aggregate upon graduation.
  • Open to BE/B.Tech, BCA, B.Sc. (Physics, Chemistry, Maths, Stats, CS, IT), BBA, B.Com. with Maths, B.A. Eco with Maths, MCA, M.Sc IT, and MBA graduates.

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  • Pay fees

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