Intro to Data Analytics, SQL, and EDA Using Python

This course is part of How to Use Data Specialization

Instructor: Brandon Krakowsky

Access provided by ENSI

3 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

Beginner level

Recommended experience

2 weeks to complete

at 10 hours a week

Flexible schedule

Learn at your own pace

What you'll learn

Classifying and analyzing data.
Executing SQL queries to work with data.
Using Python and pandas library to manipulate and explore data.

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

8 assignments

Taught in English

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This course is part of the How to Use Data Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 3 modules in this course

The ability to understand and work with data has become increasingly important in today's world, where data is ubiquitous and valuable. This course covers a range of topics, including what data is and

its different types, what big data looks like, and how companies are using it. It also explores the fields of data analysis and data science and how the two come together. To help form the field of data analytics, we'll look at the entire data analytics process and how it works, from defining the analytics problem to interpreting and presenting the results. We'll also look at some case studies, which are presented to illustrate the application of data analytics in real-world scenarios.

The ability to understand and work with data has become increasingly important in today's world, where data is ubiquitous and valuable. The first module in this course covers a range of topics, including what data is and its different types, what "big" data looks like, and how companies are using it. It also explores the fields of data analysis and data science, and how the two come together to help form the field of data analytics.

What's included

11 videos3 readings3 assignments

11 videos Total 32 minutes

How To Use Data - Specialization Intro 6 minutes
Intro to Data Analytics, SQL, and EDA Using Python - Course Intro 1 minute
About The Instructor 2 minutes
Module 1 Intro: Data & Data Analytics, Defining the Problem 1 minute
Intro to Data & Data Analytics 8 minutes
Intro to Data Science and Data Analysis 2 minutes
Intro to Data Analytics 2 minutes
Hearst Case Study: Data Analytics Process 4 minutes
Defining the Analytics Problem 3 minutes
Felix Case Study: Defining the problem 2 minutes
💻 Codio Demo - SQL 💻 2 minutes

3 readings Total 16 minutes

Module 1 Resources 10 minutes
Programming Languages and Tools Used in This Course 5 minutes
Opt-in to Penn Engineering Online Communications 1 minute

3 assignments Total 65 minutes

Learning Check - Intro to Data 20 minutes
Learning Check - Intro to Data Analysis, Data Science, and Data Analytics 20 minutes
Assignment 1 - Retention Rate Increase 25 minutes

There are multiple ways of storing and accessing data, with a variety of deployment strategies and storage options, including databases, data warehouses, and data lakes. In week 2, we’ll look at accessing data in a database. We’ll provide some context around relational databases, and then do a deep dive into SQL, which is a query language used for accessing and updating databases.

What's included

22 videos8 readings2 assignments4 app items

22 videos Total 61 minutes

Module 2 Intro: Intro to Data Wrangling using SQL 1 minute
Intro to SQL 2 minutes
Overview of Relational Databases 2 minutes
💻 Coding demo: Connecting to SQLite Database in DBeaver 💻 1 minute
Intro to Selecting and Querying Data 1 minute
💻 Coding demo: Basic SELECT Statements 💻 3 minutes
Common Comparison Operators 1 minute
💻 Coding demo: Filtering Records and Sorting Data 💻 4 minutes
Tables in Example2 Database - video for completing the assignments 1 minute
Joining Data 2 minutes
Primary Keys and Foreign Keys for Tables in Example2 Database 1 minute
💻 Coding Demo: INNER JOIN and LEFT JOIN 💻 6 minutes
Single-Row Functions 2 minutes
💻 Coding Demo: Single-Row Functions 💻 7 minutes
Group Functions 1 minute
💻 Coding Demo: Group Functions💻 6 minutes
Creating Data 3 minutes
💻 Coding Demo: CREATE Table and INSERT INTO 💻 6 minutes
Importing and Exporting Data 2 minutes
💻 Coding Demo: Loading Data in SQLite 💻 1 minute
Formatting Data 2 minutes
💻 Coding Demo: Formatting Data 💻 6 minutes

8 readings Total 80 minutes

Module 2 Resources 10 minutes
Ways to Store Data 10 minutes
Getting Started With DBeaver 10 minutes
Executing SQL with Keyboard Shortcuts 10 minutes
RIGHT JOIN 10 minutes
Single-Row Function Syntax 10 minutes
Additional Group Function Syntax 10 minutes
Updating and Deleting Data 10 minutes

2 assignments Total 60 minutes

Learning Check - Relational Databases 30 minutes
Learning Check - MySQL 30 minutes

4 app items Total 240 minutes

Assignment 2 - Creating, Updating, and Deleting Data 60 minutes
Practice Assignment: Selecting and Filtering Records 60 minutes
Practice Assignment: Basics of Joining Data 60 minutes
Practice Assignment: Single Row and Group Functions 60 minutes

Real-world problems are often hidden behind large amounts of data. Through exploratory data analysis (EDA), we can distill valuable information from data and make reliable predictions about it. In other words, Python and data analytics provide computer scientists with effective tools for understanding, processing, and utilizing real-world data. This module will take an in-depth look at how to use the powerful Python libraries pandas and NumPy to perform key tasks such as loading, querying, cleaning, summarizing, and visualizing data.