AI-powered learning
Save this course
Data Science for Non-Programmers
Discover how to conduct data analysis in Python without prior programming experience. Discover Python basics, data preprocessing, EDA, and predictive analytics for solving business problems.
4.8
70 Lessons
13h
Updated 1 month ago
Join 3 million developers at
Join 3 million developers at
LEARNING OBJECTIVES
- Differentiate data science from business intelligence and explain its interdisciplinary purpose
- Apply the data science lifecycle to define problems, clean data, run EDA, and make predictions
- Write basic Python code using variables, operators, conditionals, loops, lists, and functions
- Use pandas to import CSVs and perform indexing, filtering, apply, grouping, and pivot tables
- Clean datasets by handling missing values, duplicates, inconsistent entries, and outliers in pandas
- Create and interpret EDA visualizations and correlations using matplotlib, seaborn, and heatmaps
- Build and evaluate inference and ML models (t-tests, regression, trees, SVM, K-means) in Python
Learning Roadmap
1.
What is Data Science
What is Data Science
Get familiar with the interdisciplinary study of data, data science lifecycle, and Python's key role.
2.
Python Basics
Python Basics
Unpack the core of Python syntax, variables, operators, conditionals, functions, loops, and modules.
3.
Handling Tabular Data in Python
Handling Tabular Data in Python
10 Lessons
10 Lessons
Master the steps to handle, manipulate, and visualize tabular data using Pandas in Python.
4.
Data Cleaning
Data Cleaning
9 Lessons
9 Lessons
Grasp the fundamentals of data cleaning, including handling missing values, duplicates, inconsistencies, and outliers.
5.
Exploratory Data Analysis
Exploratory Data Analysis
8 Lessons
8 Lessons
Dig into understanding datasets, analyzing variables, and discovering trends and relationships.
6.
Statistical Inference
Statistical Inference
6 Lessons
6 Lessons
Simplify complex topics of statistical inference, including estimation, confidence intervals, and hypothesis testing.
7.
Predictive Models
Predictive Models
11 Lessons
11 Lessons
Build on creating, optimizing, and evaluating predictive models using linear and logistic regression.
8.
Machine Learning
Machine Learning
11 Lessons
11 Lessons
Sharpen your skills in machine learning algorithms, pipelines, and practical applications using Python.
Certificate of Completion
Showcase your accomplishment by sharing your certificate of completion.
Complete more lessons to unlock your certificate
Developed by MAANG Engineers
ABOUT THIS COURSE
Ready to move past Excel for complex business analysis? Then you’ll find this course very helpful.
This hands-on introductory Data Science course is aimed at professionals and students who don't have any experience with programming. It will help you advance your career by preparing you to conduct meaningful data analysis in Python on any dataset — large or small.
You’ll begin with the fundamentals of Python, with focus on CSV files in Python, covering concepts like data preprocessing and Exploratory Data Analysis (EDA). In the second half, you'll focus on predictive and inferential analysis using statistical and machine learning techniques, and learn how these techniques can help solve business problems.
Trusted by 3 million developers working at companies
A
Anthony Walker
@_webarchitect_
E
Evan Dunbar
ML Engineer
S
Software Developer
Carlos Matias La Borde
S
Souvik Kundu
Front-end Developer
V
Vinay Krishnaiah
Software Developer
Built for 10x Developers
No Passive Learning
Learn by building with project-based lessons and in-browser code editor
Personalized Roadmaps
The platform adapts to your strengths & skills gaps as you go
Future-proof Your Career
Get hands-on with in-demand skills
AI Code Mentor
Write better code with AI feedback, smart debugging, and "Ask AI"
MAANG+ Interview Prep
AI Mock Interviews simulate every technical loop at top companies
Free Resources
