Data Science & Analytics with Python Data Science & Analytics
Data Science & Analytics

Data Science & Analytics with Python

Analyse, visualise and model data with Python, pandas and scikit-learn

6 Chapters 8 Assessments 6 Weeks Certificate on Completion
About This Course

Data Science & Analytics with Python is a hands-on course for aspiring data analysts and data scientists. You will work through the complete data workflow — from collecting and cleaning raw data, to visualising insights, applying statistics and building machine learning models with Python, pandas, matplotlib, seaborn and scikit-learn.

The course closes with a capstone project in which you analyse a real dataset from start to finish, producing a polished, reproducible analysis notebook.

What You'll Learn
Conduct a complete data analysis workflow using Jupyter notebooks
Load, clean, transform and wrangle tabular data with pandas
Explore and communicate data using matplotlib and seaborn visualisations
Apply descriptive statistics, distributions and correlation to interpret data
Build and evaluate regression and classification models with scikit-learn
Split data into training and test sets and interpret model performance
Deliver an end-to-end data science project with a reproducible report
Course Chapters
Chapter 1: Data Science Fundamentals: The Data Workflow and Environment
Chapter 2: NumPy & Pandas: Dataframes, Cleaning and Wrangling
Chapter 3: Data Visualisation with matplotlib and seaborn
Chapter 4: Statistics & Probability for Data Analysis
Chapter 5: Machine Learning Basics with scikit-learn
Chapter 6: Capstone: An End-to-End Data Science Project
₹2999.00
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  • Course Content
  • 6 chapters
  • 6 weeks duration
  • Assessments
  • 8 assessments total
  • 7 written (handwritten, single submission)
  • Final project report
  • Final viva voce (oral examination)
  • Certificate
  • Perpetual certificate on completion
  • Online verification link
  • Key Policies
  • Re-registration available (unlimited, fresh start)
  • Academy terms apply — view all policies
Prerequisites
Basic familiarity with the Python programming language
Comfortable installing and running Python packages
No prior statistics or machine learning knowledge required