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Predictive Data Analysis with Python

Gain insights into performing predictive data analysis using Python. Learn about tools like NumPy, Pandas, Matplotlib, and Seaborn, and applying techniques to real-world financial and advertisement projects.

Beginner

62 Lessons

10h

Certificate of Completion

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Explanations

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Explanations

This course includes

1 Assessment

112 Playgrounds

5 Quizzes

Course Overview

Course Content

Apply Your Skills

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Course Overview

In this course, you will learn how to perform predictive data analysis using Python. The ideal audience is those who want to start their careers as data analysts. The main goal of this course is to show you how to use statistics to draw useful insights from data which can help in predicting future behavior or patterns. Beyond that, you’ll learn all the tools of the trade that data scientists use everyday including: NumPy, Pandas, Matplotlib, and Seaborn. You’ll learn not only how to extract meaningful insi...Show More

Course Content

Getting Started

1 Lessons

Get familiar with Python-based tools for effective and insightful data analysis.

What is Data Analysis?

Numpy for Python

8 Lessons

Get started with creating, indexing, transposing, and processing NumPy arrays for efficient data analysis.

What is NumPy?

NumPy Array Creation

NumPy Array Indexing

Transposing of NumPy Array

Processing NumPy Arrays

Challenge: Find Min and Max from a 2-D NumPy Array

Solution: Find Min and Max from a 2-D NumPy Array

Quiz

Pandas for Python

12 Lessons

Go hands-on with data manipulation using Pandas in Python for predictive analysis.

Select and Drop Entries in Series

Select and Drop Entries in DataFrame

Sort and Rank in Pandas

Dealing with Missing Data

Additional Functions and Features

Challenge: Summing and Swapping

Solution: Summing and Swapping

Quiz

Statistics for Data Analysis

3 Lessons

Grasp the fundamentals of statistical features, probability distributions, and the Central Limit Theorem.

Statistical Features

Probability Distributions

Central Limit Theorem

Data Wrangling

12 Lessons

Take a closer look at managing, reshaping, and cleaning data for effective analysis.

Dealing with CSV Files

Merging Data

Reshaping Data

Mapping Data and Finding Duplicates

Replace and Rename

Finding Outliers in Data

Data Grouping

Data Aggregation

Split-Apply-Combine Technique

Challenge: Clean the Data

Solution: Clean the Data

Quiz

Visualizing the Data

9 Lessons

Follow the process of using visualization tools to analyze and represent data.

Scatter and KDE Plots

Challenge: Visualizing Seaborn Datasets

Solution: Visualizing Seaborn Datasets

Quiz

Data Scraping

4 Lessons

Master the steps to scrape web data using Python and Selenium for analysis.

Project #1

6 Lessons

Try out stock market analysis, price trends, daily returns, correlations, risk, and predictions.

Stock Market Analysis

Section 1: Price Trends

Section 2: Daily Returns

Section 3: Correlation in Stocks

Section 4: Risk Estimation

Section 5: Predicting Future Stock Behavior

Project #2

5 Lessons

Unpack the core of customer behavior, brand preference, user activity, and RFM segmentation.

Customer Behavior Analysis

Section 1: Brand Analysis

Section 2: Customer Activity Analysis

Section 3: Identifying Famous Brands and Categories

Section 4: RFM Analysis

10.

Conclusion

2 Lessons

Examine essential tools, techniques, and next steps for predictive data analysis with Python.

Summary

What's Next?

Predictive Data Analysis Exam

Assessment

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