VOOZH about

URL: https://www.coursera.org/learn/pearson-data-science-fundamentals-part-1-learning-basic-concepts-data-wran-bvybr

⇱ Data Science Fundamentals Part 1: Unit 3 | Coursera

Data Science Fundamentals Part 1: Unit 3

Keep adding new skills with 10,000+ programs for $239 (usually $399). Save now.

Data Science Fundamentals Part 1: Unit 3

Included with

Ask Coursera

Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

8 hours to complete
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Beginner level

Recommended experience

8 hours to complete
Flexible schedule
Learn at your own pace

What you'll learn

  • Master the fundamentals of relational databases and persistent data storage.

  • Build and optimize ETL pipelines using Python and object-relational mappers.

  • Apply data validation techniques to ensure data quality and integrity.

  • Utilize Pandas for effective data exploration, transformation, and statistical analysis.

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

3 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Data Science Fundamentals, Part 1 Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There is 1 module in this course

This course explores the fundamentals of relational databases and how to seamlessly map Python data structures to robust database tables using object-relational mappers (ORMs). You'll gain practical experience in building efficient ETL (Extract, Transform, Load) pipelines, ensuring your data is not only accessible but also reliable and persistent. You'll learn about data validation and quality control, leveraging powerful tools like Pandas to explore, clean, and analyze your datasets. By the end of the course, you’ll be equipped to uncover insights, identify biases, and apply best practices in data management.

This module guides learners through essential data handling skills, from storing and persisting data using relational databases and object-relational mappers, to validating, exploring, and transforming data for analysis. Emphasizing practical techniques with tools like Pandas, the lessons cover best practices for querying, managing missing values, and using descriptive statistics and visualizations to understand data quality and distribution. The module provides a systematic approach to the ETL process, equipping students to efficiently prepare data for deeper analytical modeling.

What's included

28 videos3 assignments

28 videos•Total 394 minutes
  • Topics•1 minute
  • Introduction to Databases with SQLite•27 minutes
  • Inspecting Databases with the SQLite shell•13 minutes
  • The Database Landscape•12 minutes
  • What's in a Schema? Mapping Data Models to Data Tables•23 minutes
  • Introduction to Object Relational Mappers•7 minutes
  • ORMs in Python with peewee•19 minutes
  • Creating and Querying Records with peewee•25 minutes
  • End-to-end ETL in Python•9 minutes
  • Advantages and Disadvantages of ORMs•5 minutes
  • Extract, Transform, Load--Putting It All Together•10 minutes
  • Topics•1 minute
  • Introduction to Exploratory Data Analysis•17 minutes
  • Understanding your Data Quickly with Graphical Tools•17 minutes
  • Inspecting Databases and Building Schemas with peewee•20 minutes
  • Data Quality Checks with peewee•18 minutes
  • Finding Missing Data and Null Values with peewee•12 minutes
  • Dealing with Missing Data•11 minutes
  • EDA for Insight--Describing Data•5 minutes
  • Inspecting Queries and Displaying Results in peewee•18 minutes
  • Groups and Aggregates with peewee•14 minutes
  • Ranking and Sorting Venues•20 minutes
  • SQL Relations and Joins•8 minutes
  • Joins with peewee•28 minutes
  • Querying Across Datasets with Joins•26 minutes
  • Translating peewee to SQL•7 minutes
  • A Visual Introduction to Joins with SQL•15 minutes
  • Data Science Fundamentals Part 1: Sunmary•3 minutes
3 assignments•Total 90 minutes
  • Storing Data: Persistence with Relational Databases Quiz•30 minutes
  • Validating Data: Provenance and Quality Control Quiz•30 minutes
  • End of Course Assessment•30 minutes

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.

Instructors

Pearson
268 Courses•65,339 learners

Explore more from Data Analysis

Why people choose Coursera for their career

👁 Image

Felipe M.

Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
👁 Image

Jennifer J.

Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
👁 Image

Larry W.

Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
👁 Image

Chaitanya A.

"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

Frequently asked questions

To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

Financial aid available,