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Data Science for Non-Programmers
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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.

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Overview

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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.

Ready to move past Excel for complex business analysis? Then you’ll find this course very helpful. This hands-on introductory D...Show More

Content

70 Lessons5 Quizzes8 Challenges

What is Data Science

3 Lessons

Get familiar with the interdisciplinary study of data, data science lifecycle, and Python's key role.

The Buzzword "Data Science"

Data Science Lifecycle

Python for Data Science

Python Basics

12 Lessons

Unpack the core of Python syntax, variables, operators, conditionals, functions, loops, and modules.

Hello World

Variables and Data Types

Operators

Conditional Statements

Exercise: Average of a List

Solution Review: Average of a List

Exercise: Factorial of a Number

Solution Review: Factorial of a Number

Handling Tabular Data in Python

10 Lessons

Master the steps to handle, manipulate, and visualize tabular data using Pandas in Python.

Importing Data in CSV Files with Pandas

Indexing and Selection

Filtering Data

Applying Functions to Data

Aggregating Data

Grouping Data

Pivot Tables

Plotting Data 1: Univariate Plots

Plotting Data 2: Bivariate Plots

Test Your Knowledge

Data Cleaning

9 Lessons

Grasp the fundamentals of data cleaning, including handling missing values, duplicates, inconsistencies, and outliers.

Introduction to Data Cleaning

Outlier Detection and Removal

Exercise: Cleaning NYC Property Sales

Solution Review: Cleaning NYC Property Sales

Exploratory Data Analysis

8 Lessons

Dig into understanding datasets, analyzing variables, and discovering trends and relationships.

Introduction

Analyzing Individual Quantities

Exploring Categorical Quantities

Exploring Numerical Quantities

Correlation and Heatmaps

Exercise: Exploring E-Commerce

Solution Review: Exploring E-Commerce

Business Example: RFM Analysis in Python

Statistical Inference

6 Lessons

Simplify complex topics of statistical inference, including estimation, confidence intervals, and hypothesis testing.

The Basics of Statistical Inference

Predictive Models

11 Lessons

Build on creating, optimizing, and evaluating predictive models using linear and logistic regression.

A Simple Model

Model Fitting on a Loss Function

Gradient Descent

Optimization with Gradient Descent

Simple Linear Regression

Multiple Linear Regression

Evaluating Regression Models

Logistic Regression

Evaluating Logistic Regression Models

Exercise: Churn Prediction

Solution Review: Churn Prediction

Machine Learning

11 Lessons

Sharpen your skills in machine learning algorithms, pipelines, and practical applications using Python.

Why Machine Learning

Machine Learning Pipeline

Decision Trees

Random Forests

Support Vector Machines

Ensembles: Bagging vs Boosting

Clustering for Unsupervised Learning

K-Means on Two-Dimensional Data

K-Means on n-Dimensional Data

Test your Knowledge

Conclusion

How to Predict the Traffic Volume Using Machine Learning

Project

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Developed by MAANG Engineers

Every Educative resource is designed by our in-house team of ex-MAANG software engineers and PhD computer science educators — subject matter experts who’ve shipped production code at scale and taught the theory behind it. The goal is to get you hands-on with the skills you need to stay ahead in today's constantly evolving tech landscape. No videos, no fluff — just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

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Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

AI Mock Interviews

Test your skills in a simulated interview setting. Receive personalized feedback based on your performance. Available for Coding Interviews, System Design, and more.

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