Learn data analysis with Python

Data analysis is at the heart of data science, helping organisations uncover insights that drive better decisions. On this three-week course, you’ll learn how to collect, prepare, and analyse data using Python while developing practical skills used by data professionals across industries.

You’ll begin by exploring web scraping techniques to collect data from online sources before learning how to prepare datasets for analysis. Along the way, you’ll gain experience with the workflows and tools used to turn raw data into meaningful business insights.

Prepare data for analysis with confidence

High-quality analysis starts with well-prepared data. You’ll explore essential data preprocessing techniques, including handling missing values, scaling features, and encoding categorical data to create clean, reliable datasets.

These practical skills will help you understand how data is prepared for analysis and modelling, giving you the confidence to work with real-world datasets.

Create compelling data visualisations with Python

Learn how to communicate insights through clear and engaging data visualisation using two of Python’s most widely used libraries: Matplotlib and Seaborn.

You’ll create a range of visualisations before applying data storytelling principles to combine multiple visuals into audience-ready reports. You’ll also conduct exploratory data analysis to identify trends, patterns, and relationships that support data-driven decision-making.

Gain career-ready skills from experienced data science professionals at Edureka

Throughout the course, you’ll learn from the experts at Edureka to develop the data analysis and data visualisation skills employers value. With this knowledge, you’ll be prepared for future roles in data science, data analytics, and business intelligence.

Syllabus

Week 1
Data Acquisition and Preprocessing
- Foundations of Data Analysis
  Explore how raw data becomes reliable evidence by examining the data analysis process, key quality checks and the decisions that shape trustworthy insights.
- Collecting Data with Web Scraping
  Capture valuable web data using Requests and BeautifulSoup, while applying responsible scraping practices to organise information for reliable analysis.
- Handling Missing Data and Feature Scaling
  Refine dataset quality by treating missing values and scaling numerical features to create consistent, analysis-ready data.
- Encoding and Preparing Analysis-Ready Data
  Prepare raw data for reliable analysis by encoding categorical features and combining preprocessing steps into a structured, reusable workflow.
Week 2
Data Visualisation and Storytelling
- Visualisation with Matplotlib
  Visualise data clearly with Matplotlib by creating charts that reveal trends, comparisons and distributions.
- Statistical Visualisation with Seaborn
  Reveal deeper patterns in data with Seaborn by examining distributions, relationships and polished multi-plot visualisations.
- Data Storytelling and Visual Reporting
  Communicate analytical findings effectively by combining visuals into coherent narratives, reports and dashboard-style summaries.
Week 3
Exploratory Data Analysis and Insight Presentation
- The EDA Workflow
  Investigate datasets systematically by profiling data quality, examining distributions and relationships, and using visual evidence to uncover meaningful patterns.
- End-to-End Data Analysis Project
  Synthesize the complete data analysis workflow by preparing real-world data, generating evidence-based insights and presenting findings for a clear audience and purpose.

Prove you're job ready

Highlight the new, job-relevant skills you’ve gained and supplement existing qualifications with a hard-earned, industry-specific digital certificate – plus one for every course within your ExpertTrack.

Learn the latest in your chosen industry or subject.
Complete each course and pass assessments.
Receive certificates validated by the educating organisation.
Impress employers with learning outcomes you can add to your CV.
Make your career dreams a reality.

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Learning on this course

On every step of the course you can meet other learners, share your ideas and join in with active discussions in the comments.

What will you achieve?

By the end of the course, you‘ll be able to...

Explain key principles of responsible data collection, preprocessing, visualisation, and exploratory data analysis.
Apply Python techniques to collect, clean, scale, encode, and prepare data for analysis.
Investigate datasets using exploratory analysis and statistical visualisation to identify patterns, relationships, and data-quality issues.
Evaluate appropriate charts, visualisation techniques, and reporting approaches for different analytical questions and audiences.
Create clear, audience-ready visual reports and data stories that communicate evidence-based insights effectively.

Who is the course for?

This course is designed for aspiring data professionals, software developers, analysts, engineers, and business professionals who want to build practical data science skills with Python. No prior data science or machine learning experience is required, though basic computer literacy and comfort with logical problem-solving will be helpful.

It is ideal for career changers moving into data roles, working professionals looking to add analytics capabilities to their current role, and graduates preparing for data analyst, data scientist, or machine learning engineer positions. It is also valuable for managers and domain experts who want to understand how data-driven decisions are made.

Who will you learn with?

Edureka Instructors

Who developed the course?

Edureka

Edureka is a global online learning platform offering industry-focused training in emerging technologies such as Cloud, AI, GenAI, Data Science, DevOps, and Cybersecurity, helping professionals upskill and advance their careers.

About this ExpertTrack

Build job-ready data science expertise with Python to analyse data, build machine learning models and deploy AI-powered solutions.

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After your free trial you can:

Pay $39 per month to keep learning online
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Work at your own pace and set your own deadlines at every stage
Only pay while you’re learning; the subscription will cancel automatically when you finish
Complete online assessments to test your knowledge and prove your skills
Earn digital course certificates and a final award that you can share online, with potential employers, and your professional network
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