Data Science and Machine Learning
Data Science Fundamentals
Enter the world of data. Learn the data science workflow, tools, and thinking needed to turn raw data into valuable insights.
USD 49
Data Science and Machine Learning
Data Analysis with Python and Pandas
Load, clean, reshape, analyse and chart real business data in Python with pandas, NumPy, Matplotlib and Seaborn, and turn it into clear findings.
About this course
Analyze data like a pro. Use Python, Pandas, and NumPy to clean, transform, and explore datasets and extract meaningful findings.
What you will learn
- Set up a reproducible Python analysis environment with Jupyter notebooks and a clean project structure
- Import CSV, Excel and SQL data into pandas with correct data types, dates and identifiers
- Clean messy data by handling missing values, fixing types, removing duplicates and standardising text
- Summarise and compare groups with groupby, pivot tables and transform
- Combine and reshape datasets safely with validated merges, concat, melt and pivot
- Explore a dataset systematically and present findings with honest Matplotlib and Seaborn charts
Curriculum
Module 1Python for Data4 lessons
- 1Python Setup and Notebooks Free preview
- 2Python Refresher for Analysis
- 3NumPy Arrays Essentials
- 4Reading Data: CSV, Excel, SQL
- QModule quiz (4 questions)
Module 2Pandas Core4 lessons
- 5DataFrames and Series
- 6Selecting and Filtering Data
- 7Handling Missing Values
- 8Data Types and Conversions
- QModule quiz (4 questions)
Module 3Transforming Data4 lessons
- 9GroupBy: Split, Apply, Combine
- 10Merging and Joining Datasets
- 11Reshaping: Pivot and Melt
- 12Dates, Times and Strings
- QModule quiz (4 questions)
Module 4Analysis Workflows3 lessons
- 13EDA Workflow on a Real Dataset
- 14Visualisation with Matplotlib and Seaborn
- 15Course Project: Sales Data Analysis
- QModule quiz (4 questions)
PFinal project: Sales Data Analysis for a Household Goods Distributor
Who this course is for
- Beginners who know a little Python and want to analyse data with it
- Excel users ready to move repeatable reporting into Python
- Business, finance and operations staff who work with sales or transaction data
Requirements
- A computer (Windows, macOS or Linux) where you can install Python, or a Google account to use Colab
- Basic Python: variables, lists and simple functions (refreshed in Module 1)
- No prior experience with pandas or NumPy is needed
What is included
Written lessons
15 lessons, each with a practical exercise and key points to remember.
Module quizzes
A short quiz at the end of each module. Pass mark 70%, and you can retake it.
Final project
Sales Data Analysis for a Household Goods Distributor. A practical brief with steps and a way to check your own work.
Certificate
A certificate of completion from EMFAD Courses with a unique code anyone can verify.
How the certificate works
Complete every lesson and pass every module quiz with 70% or more. Your certificate then appears in your learner area, ready to print or save as PDF. It shows your name, the course title, the completion date and a unique code. It is a certificate of completion from EMFAD Courses, not an accredited qualification.
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