Python fundamentals
Introduction to Python, data types, operators, and expressions
Hands-onWrite scripts to perform simple calculations, create a personal expense tracker
Level 1 · Beginner
Python for AI and Data Science Course: Python for AI & Data Science
Python, NumPy, Pandas, visualisation, statistics and machine learning concepts for complete beginners. Write Python confidently, analyse and visualise data, apply core statistics and frame problems for machine learning.
LevelBeginner
Duration40 live hours
Hands-onAbout 80%
Modules12
Who it is for
Is this level right for you?
Students, freshers, analysts and career switchers with no coding background.
Tools you will use
PythonNumPyPandasMatplotlibSeaborn
Syllabus · 12 modules · 40 hours
Python for AI & Data Science syllabus
2 h
Control Flow
Conditional statements, loops, and logical operators
Hands-onBuild a basic menu-driven ATM simulation
Data Structures
Lists, tuples, dictionaries, sets, and their operations
Hands-onCreate a student gradebook system
Functions & Modules
Creating and using functions, importing modules, Python standard library
Hands-onDevelop a math helper tool with reusable functions
File Handling
Reading and writing text/CSV files
Hands-onBuild a CSV-based contact management app
NumPy (Data Analysis)
Arrays, indexing, slicing, basic operations
Hands-onPerform climate data analysis using sample temperature datasets
Pandas (Data Manipulation)
DataFrames, series, loading and cleaning data
Hands-onAnalyze a retail sales dataset for top products
Matplotlib & Seaborn (Data Visualization)
Basic plots, histograms, scatter plots and advanced plot visualizations using Matplotlib, and Seaborn
Hands-onVisualize rainfall patterns over time using real weather data Create a financial performance dashboard from stock data
Essential Math & Statistics for AI
Algebra refresher, functions, vectors and statistics basics, Vectors, matrices, matrix operations, determinants Probability rules, mean, median, mode, variance, standard deviation, Z-Score, p-value, significance level, T-Test, Z-Test, ANOVA, Probability, Events
Hands-on-
Introduction to Machine Learning Concepts
What is AI/ML, types of ML, supervised vs unsupervised
Hands-onClass discussion: Identify real-life applications of AI across industries
Mini Project: Beginner Level
Capstone Project: Build a Calculator In Python
Hands-onCapstone Project: Build a Python App which functions as a Calculator
Capstone Project: Beginner Level
Apply Python and math basics to a real-world problem
Hands-onRetail Inventory Tracker: Build a Python app that reads sales data from a CSV, identifies best-selling products, and predicts restocking needs
Full syllabus
See all 12 modules
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FAQ
Questions about this level
How long is the python for ai and data science course?
40 hours of live, instructor-led training, of which about 32 hours are hands-on labs, projects and a capstone.
Who is this level for?
Students, freshers, analysts and career switchers with no coding background.
What will I be able to do after this level?
Write Python confidently, analyse and visualise data, apply core statistics and frame problems for machine learning.
Which tools will I use?
Python, NumPy, Pandas, Matplotlib and Seaborn.
Get in touch
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