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Statistical Analysis and Modeling Using SQL and Python

Development Academy of the Philippines
Enrollment is Closed

Course Overview

SQL is a dominant data analysis language since data are usually available in a structured, database format. Most analyses involve a lot of filtering, grouping, sorting, and aggregation, for which SQL is quite handy to use. Python, on the other hand, has well-known libraries, specially designed for data analysis and statistical modeling. This course teaches how to perform descriptive, diagnostic, and predictive analytics using functions, procedures, and best practices in both SQL and Python. Combining the use of SQL to retrieve and process the essential data for analysis, together with the use of specialized Python libraries for more complex data manipulation, analysis, and modeling is also discussed.

What You Will Learn

Upon completion of this course, the learners are expected to:

  • leverage the powerful combination of SQL and Python to efficiently perform analysis and modeling; and
  • apply the appropriate analytics and modeling techniques in solving business problems.

Course Requirement

You will need a computer or laptop with PostgreSQL installed.

Note to SPARTA scholars: Upon enrollment, you will have 6 months to finish a SPARTA course. Failure to complete the course in 6 months and/or inactivity for 3 months will result in course access revocation.

Course Instructor

Course Staff Image #1

Raymond Freth Lagria

Subject Matter Expert

Course Content

Week 1: Recipes for Data Analysis in SQL

15 Videos | 4 Activities

15 Videos

  • Welcome to the course!
  • SQL Aggregation Functions
  • Complex Subqueries
  • Common Table Expressions
  • Calculating Running Total
  • ROW Number Functions
  • RANK and DENSE RANK Function
  • LAG Function
  • Calculating Running/ Moving Average and the Weighted Moving Average
  • Calculating Exponential Moving Average with Recursive CTEs
  • Difference from the First Value and the Last Value
  • Calculating Month-Over-Month Growth Rate
  • Calculating Top N Items Per Group
  • Calculating Percentage of Total Sum and Summary Statistics

4 Activities

  • Recall Activities (3)
  • Quiz

Week 2: Recipes for Data Analysis in Python

8 Videos | 3 Activities

8 Videos

  • NumPy 1 (Basic NumPy)
  • NumPy 2 (Data Types)
  • NumPy 3 (Statistical Functions)
  • Pandas 1 (Data Frames)
  • Pandas 2 (Column and Row Operations)
  • Pandas 3 (Aggregating Operations)
  • Pandas 4 (Merging Operations)
  • Pandas 5 (Other Operations)

3 Activities

  • Recall Activities (2)
  • Quiz

Week 3: Basic Statistics in Python

6 Videos | 2 Activities

6 Videos

  • Measures of Central Tendency and Dispersion
  • Measures of Association (Data Types)
  • Frequency Distribution
  • Introduction to Hypothesis Testing
  • Hypothesis Testing in Python 1
  • Hypothesis Testing in Python 2

2 Activities

  • Recall Activity
  • Quiz

Week 4: Applications in Descriptive, Diagnostic, and Predictive Analytics Use-Case

8 Videos | 3 Activities

8 Videos

  • Descriptive Analytics
  • Diagnostic Analytics
  • House Prices - Descriptive Analytics Example
  • Market Basket Analysis
  • Market Basket Analysis Example
  • Introduction to Predictive Analytics
  • Predictive Analytics Use-Case
  • Key Takeaways

3 Activities

  • Recall Activity
  • Quiz
  • Final Exam
  1. Course Number

  2. Classes Start

  3. Classes End

  4. Estimated Effort

    1-2 hours/week (8 hours)
  5. Price