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Scripting with Python and SQL for Data Engineering

In this course, part of the Python, Bash and SQL Essentials for Data Engineering Specialization, you will gain the skills to work effectively with data using Python and SQL. You will learn to:

Leverage Python's powerful data structures to load, manipulate, and analyze data
Create robust Python scripts to automate data processing tasks
Utilize SQLite to store and retrieve data from within your Python scripts
Extract data from websites using web scraping techniques and persist it in databases
Work with MySQL databases using modern tools like VSCode to execute queries and manage data

Whether you are a data engineer, analyst, or aspiring data professional, this course will equip you with the essential skills to efficiently handle data and drive meaningful insights in today's data-driven world.

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What's inside

Learning objectives

Manipulate data using python's built-in data structures
Create python scripts to automate data tasks
Use sqlite to store and query data in python

Extract data from websites via web scraping
Execute mysql queries and operations in vscode
Import and export data in mysql databases

Manipulate data using python's built-in data structures
Create python scripts to automate data tasks
Use sqlite to store and query data in python
Extract data from websites via web scraping
Execute mysql queries and operations in vscode
Import and export data in mysql databases

Syllabus

Here is the course structure formatted with bullets for each module:

Module 1: Working with Data in Python (5 hours)

\- Videos (Total 62 minutes):

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Read about what's good

what should give you pause

and possible dealbreakers

Designed for beginners, this course lays the foundational knowledge and core skills for those seeking to enter the field of data engineering

Taught by experienced professionals in data engineering, this course conveys real-world applications and practical techniques

Delves into the practical applications of Python, Bash, and SQL, equipping learners with industry-standard tools for data analysis and engineering

May require supplemental learning for those with limited programming experience, as it assumes some prior knowledge

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Reviews summary

Practical python and sql for data engineering

According to students, this course receives largely positive feedback, consistently praised for its practical, real-world applicability and effective instruction. Learners particularly value the hands-on labs and the comprehensive coverage of essential topics like Python scripting, SQLite, web scraping, and MySQL. While many find the course well-structured and foundational for data engineering, some reviewers noted the pace can be fast and it may assume prior Python knowledge, making it more suitable for those with a basic understanding than complete beginners.

Provides a solid base in Python, SQL, and web scraping.

"Offers an excellent foundational understanding for aspiring data engineers."

"The course comprehensively covers essential tools like SQLite, MySQL, and web scraping."

"I now have a solid foundation in scripting and database integration for data engineering roles."

Instructor provides clear, concise, and knowledgeable explanations.

"The instructor is clear, concise, and explains complex concepts really well."

"Alfredo Deza is fantastic; his explanations are easy to follow and very helpful."

"I found the instructor very effective in conveying the core ideas of the course."

Labs are highly effective for reinforcing concepts.

"The hands-on labs effectively reinforce learning, making the concepts stick."

"The Jupyter notebooks and practical projects are the strongest part of the course for me."

"I appreciated the ungraded labs; they were key to solidifying my understanding of the material."

Delivers immediately applicable skills for data engineering.

"This course is very practical and immediately applicable to real-world scenarios."

"Extremely useful. It covers scripting, databases, and offers real-world applications."

"I learned how to automate data processing tasks, which has been incredibly useful in my work."

Course pace can be fast, requiring prior Python and SQL basics.

"I felt the course was rushed, and some explanations were superficial, requiring prior Python knowledge."

"This course assumes too much prior knowledge, making it challenging for true beginners."

"I found the pace a bit too quick, especially in certain sections; I had to rewatch videos multiple times."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Scripting with Python and SQL for Data Engineering with these activities:

Join a study group or online forum for Python and data engineering discussions

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Engage with peers and experts in the field by actively participating in discussions, sharing knowledge, and collaborating on projects.

Browse courses on Python

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Identify and join relevant study groups or online forums
Participate in discussions, ask questions, and share your insights
Collaborate on projects or group challenges

Review basic Python skills

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Let's brush up on the fundamentals of Python programming to ensure you have the necessary foundational skills for this course.

Browse courses on Python

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Review variables and data types
Practice writing and executing simple Python scripts
Create a few basic functions and classes

Complete an online Python tutorial

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Deepen your understanding of Python by following a guided tutorial that covers data structures and their applications.

Browse courses on Python

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Identify a reputable online tutorial or course
Follow the tutorial step-by-step, practicing the concepts
Complete any exercises or assignments provided in the tutorial

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Attend a Python workshop focused on data engineering

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Advance your knowledge and skills in Python and data engineering by attending a specialized workshop led by industry experts.

Browse courses on Python

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Research and identify relevant workshops
Register and attend the workshop
Actively participate in discussions, demos, and hands-on exercises

Solve Python coding challenges

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Challenge yourself with Python coding challenges to reinforce your grasp of data structures and algorithms.

Browse courses on Python

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Join an online coding platform like LeetCode or HackerRank
Select coding challenges appropriate to your skill level
Solve the challenges, referring to documentation or online forums when needed

Create a Python script to automate a data processing task

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Solidify your Python skills by creating a project that leverages data manipulation and automation techniques.

Browse courses on Python

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Identify a data processing task that can be automated
Design a solution using Python and appropriate libraries
Write the Python script, incorporating functions and data structures as needed
Test and refine the script to ensure accurate and efficient data processing

Develop a dashboard to visualize data using Python

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Combine your Python skills with data visualization techniques to create an interactive dashboard that effectively communicates data insights.

Browse courses on Python

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Gather and clean the necessary data
Choose an appropriate Python library for data visualization
Design and develop the dashboard layout and visualizations
Deploy the dashboard for sharing and presentation

Participate in a Python-based hackathon or competition

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Engage in a competitive environment to showcase your Python skills and expand your knowledge in practical applications of data science or machine learning.

Browse courses on Python

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Identify and register for an appropriate hackathon or competition
Form a team or work individually on the challenge
Develop a solution using Python and relevant technologies
Present or submit your solution for evaluation

Career center

Learners who complete Scripting with Python and SQL for Data Engineering will develop knowledge and skills that may be useful to these careers:

Reading list

We've selected 50 books that we think will supplement your learning. Use these to develop background knowledge, enrich your coursework, and gain a deeper understanding of the topics covered in Scripting with Python and SQL for Data Engineering.

MySQL Reference Manual

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The official manual for MySQL, providing comprehensive documentation on all aspects of the database, including installation, configuration, operations, and troubleshooting. It is an essential reference for anyone working with MySQL.

Scripting with Python and SQL for Data Engineering

What's inside

Learning objectives

Syllabus

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Reviews summary

Practical python and sql for data engineering

Activities

Career center

Reading list

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