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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

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.
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Explanations

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This course includes

1 Assessment
112 Playgrounds
5 Quizzes
Course Overview
Course Content
Apply Your Skills
Recommendations

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
In this course, you will learn how to perform predictive data analysis using Python. The ideal audience is those who want to sta...Show More

TAKEAWAY SKILLS

Analysis Tools

Data Extraction

Data Statistics

Data Cleaning

Data Manipulation

Data Visualization

Insights Extraction

Course Content

1.

Getting Started

1 Lessons

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

4.

Statistics for Data Analysis

3 Lessons

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

7.

Data Scraping

4 Lessons

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

8.

Project #1

6 Lessons

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

9.

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.

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