Data Science and Machine Learning
Data Analysis with Python and Pandas
Analyze data like a pro. Use Python, Pandas, and NumPy to clean, transform, and explore datasets and extract meaningful…
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Data Science and Machine Learning
Data Science Fundamentals
Take a real business question from raw data to an honest, clearly presented recommendation using the core data science workflow and Python.
About this course
Enter the world of data. Learn the data science workflow, tools, and thinking needed to turn raw data into valuable insights.
What you will learn
- Turn a vague business goal into a specific, measurable question that data can answer
- Import, check and clean messy data from spreadsheets, databases and exported files using pandas
- Explore data with summary statistics and charts to find patterns, errors and useful features
- Build and honestly evaluate simple predictive models, including correlation, linear regression and a decision tree
- Present findings to non-technical audiences with truthful charts and clear recommendations
- Identify sources of bias and privacy risk in data work and apply practical safeguards
Curriculum
Module 1The Data Science Landscape4 lessons
- 1What Data Scientists Actually Do Free preview
- 2The Data Science Workflow
- 3Types of Data and Where It Lives
- 4Tools of the Trade Overview
- QModule quiz (4 questions)
Module 2Working with Data4 lessons
- 5Collecting and Importing Data
- 6Cleaning Messy Data
- 7Exploratory Data Analysis
- 8Feature Thinking: What Matters in Data
- QModule quiz (4 questions)
Module 3Analysis and Modelling4 lessons
- 9Descriptive Statistics in Practice
- 10Correlation and Simple Prediction
- 11Introduction to Machine Learning Ideas
- 12Evaluating Results Honestly
- QModule quiz (4 questions)
Module 4Communicating Insights4 lessons
- 13Charts That Tell the Truth
- 14Presenting Findings to Non-Technical Audiences
- 15Ethics and Bias in Data
- 16Course Project: End-to-End Mini Analysis
- QModule quiz (4 questions)
PFinal project: End-to-End Mini Analysis: From Question to Recommendation
Who this course is for
- Complete beginners who want to understand how data science works in practice
- Analysts, managers and business owners who want to make better decisions with their data
- Students and career changers preparing for entry-level data roles
Requirements
- A computer where you can install Anaconda or Python, or a Google account to use Google Colab
- Comfort with basic spreadsheets and school-level arithmetic; no prior programming is required, but a little Python helps
- A willingness to practise with small datasets of your own or from public sources
What is included
Written lessons
16 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
End-to-End Mini Analysis: From Question to Recommendation. 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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