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

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

1 Assessment

112 Playgrounds

5 Quizzes

This course includes

1 Assessment

112 Playgrounds

5 Quizzes

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

TAKEAWAY SKILLS

Analysis Tools

Data Extraction

Data Statistics

Data Cleaning

Data Manipulation

Data Visualization

Insights Extraction

Course Content

Getting Started

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

What is Data Analysis?

Numpy for Python

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

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

What is Pandas?Series in Pandas DataFrame in Pandas Reindex Objects 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

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

Statistical Features Probability Distributions Central Limit Theorem

Data Wrangling

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.

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.

Project #2

5 Lessons

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

10.

Conclusion

2 Lessons

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

Predictive Data Analysis Exam

Assessment

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