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Data Analysis Real world use-cases- Hands on Python
Rating: 4.6 out of 5(1,241 ratings)
70,231 students

Data Analysis Real world use-cases- Hands on Python

Build 5 Data Analysis Projects and Data Analyst Projects in Python to Create Job-Ready Data Analytics Portfolio
Created byShan Singh | 300,000+ Students | Best-Selling Instructor
Last updated 4/2026
English

What you'll learn

  • Build a job-ready portfolio by completing 5 real-world Data Analysis Projects and Data Analyst Projects in Python.
  • Understand the complete Data Analytics pipeline — import, clean, merge & analyze data.
  • Solve real business problems using Data Analytics Projects with Python libraries (Pandas, NumPy, visualization tools)
  • Master Pandas, NumPy, Seaborn, Matplotlib, Plotly, Folium & WordCloud packages for Data Analysis
  • Learn how to work with Excel, Text, Time Series & Geographical Data in Python.
  • Apply Data Analysis techniques to solve real-world business problems.

Course content

9 sections • 60 lectures • 8h 4m total length

  • Intro to this course3:59
  • Utilize QnA of the course ( Golden Oppurtunity ) !1:14
  • How to follow this course-Must Watch1:27
  • Installation of Anaconda Navigator2:53

    Here’s a step-by-step guide to install it on Mac or Windows:

    Step 1: Download the Anaconda Installer

    1. Go to the official Anaconda Downloads Page

    2. Choose the installer for your operating system:

      • Windows: .exe file.

      • macOS: .pkg file.

      • Select the installer that matches your system (64-bit for most systems)..


    Step 2: Start the Installation

    For Windows:

    1. Double-click the .exe installer file.

    2. Follow the installation prompts:

      • Installation Type: Choose "Just Me" (recommended for most users).

      • Destination Folder: Use the default or select a custom location.

      • Advanced Options:

        • Check "Add Anaconda to my PATH environment variable" (optional but useful for command-line use).

        • Leave "Register Anaconda as my default Python" checked.

    3. Click Install to begin the installation process.

    For macOS:

    1. Double-click the .pkg installer file.

    2. Follow the instructions in the installer:

      • Select the installation location (use the default or choose a custom folder).

      • Click Install to proceed.

    3. Enter your Mac password if prompted..


    Step 3: Complete the Installation

    • Once the installation is complete, click Finish (Windows) or close the installer (macOS).

    • On Windows, you may need to restart your computer to finalize the setup..


    Step 4: Launch Anaconda Navigator

    1. Windows:

      • Search for "Anaconda Navigator" in the Start Menu and click to open it.

    2. macOS:

      • Open Launchpad, find Anaconda Navigator, and click it to launch.


    Note : if u are facing any issues , kindly do let us know !

  • Quick Summary of Jupyter Notebook5:47

Requirements

  • You will need to install Anaconda. We will show you how to do it in one of the first lectures of the course

Description

This course helps you build hands-on Data Analytics Projects using Python — step by step, from beginner to job-ready Data Analyst..

You’ll work on real-world datasets and complete end-to-end data analyst project workflows (cleaning, EDA, visualization, insights, reporting).



Student Testimonials:

Shan Singh is absolutely amazing! Step-by-step projects with clear explanations. Easy to understand. Real-world Data Analytics project. Simply the best course on Data Analysis that I could find on Udemy! After the course you can easily start your career as a Data Analyst. - Nicolas Ray


This is the best course for people who have just learnt Python basics (experienced for this course) and want to become Data Analysts or Data Scientists. This will act as a bridge between fundamental theoretical Python concepts and its application by using smart data analysis project. - Mitra Rajdev


Very good course, on one side the instructor elaborates on technical general knowledge like what is integer or signed/unsigned and how it works and on the other side he is very short and to the chase with the Python commands and the requirements execution. - Tali Fong


Superb... what a good soul he is. His voice is filled with love and humbleness and understanding... he knows the pains of a beginner... when he explains it feels like he is explaining to a 5-year-old kid.




Can you start right now?

A frequently asked question of Python Beginners is: "Do I need to become an expert in Python coding before I can start working on Data Analysis Projects?"

The clear answer is: "No

  • You just require some Python Basics like data types, simple operations/operators, lists and numpy arrays that you can learn from my Free Python course 'Basics Of Python'

If you want to use Python for Data Science, Data Analytics, or as a replacement for Excel, this course is the perfect starting point.



Why should you take this Course?

  • Real-World Data Analytics Projects — not toy datasets !

    You’ll work on end-to-end Data Analysis Projects that reflect real business challenges and industry datasets.


  • Complete Data Analysis Workflow

    From importing messy data → cleaning, merging, and transforming → performing Exploratory Data Analysis (EDA) → visualizing insights using Pandas, Matplotlib, Seaborn, and Plotly.


  • Hands-On Learning Approach —

    Practice every concept with guided coding exercises and Data Analytics Projects in Python.


  • Business + Technical Focus —

    Understand not only how to code but also why certain decisions are made in real Data Analysis Projects


  • Portfolio-Ready Projects —

    By the end, you’ll have multiple Data Analyst Projects to showcase on your resume or GitHub — perfect for your Data Analyst portfolio.


  • Guaranteed Satisfaction: Otherwise, get your money back with 30-Days-Money-Back-Guarantee.


Who this course is for:

  • Everyone who want to step into Data Analytics or Data Analysis !
  • Aspiring Data Analysts who want to work on real-world Data Analytics Projects for their portfolio..
  • Data Scientists/Data Analyst who want to improve their Data Handling/Manipulation/Analysis skills.
  • Anyone interested in mastering real-world Data Analysis Projects using Pandas, Seaborn, and Plotly.
  • Students preparing their Data Analyst Project Portfolio to get job-ready in the field of Data Analytics.

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