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 insights from data, but you’ll also learn how to create stunning visualizations that you can use for reports.
Various datasets of real-world scenarios are used in each lesson to get you accustomed to handling any type of data. At the end of the course, you will work on two real-world projects that demonstrate how data analysis techniques are being used in the financial and advertisement sector to generate revenue.
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
Content
2.
Numpy for Python
8 Lessons
Get started with creating, indexing, transposing, and processing NumPy arrays for efficient data analysis.
3.
Pandas for Python
12 Lessons
Go hands-on with data manipulation using Pandas in Python for predictive analysis.
4.
Statistics for Data Analysis
3 Lessons
Grasp the fundamentals of statistical features, probability distributions, and the Central Limit Theorem.
5.
Data Wrangling
12 Lessons
Take a closer look at managing, reshaping, and cleaning data for effective analysis.
6.
Visualizing the Data
9 Lessons
Follow the process of using visualization tools to analyze and represent data.
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.
Certificate of Completion
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