Data Engineering for Beginners with Python and SQL

Focused View

Kiril Spiridonov

2:16:38

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1. Python Basics For Data Engineers

1. Welcome!.mp4

04:48

2. Getting Started.mp4

17:10

3. Data Types.mp4

11:05

4. Strings.html

5. Integers.html

6. Conditional Statements.mp4

15:54

7. Lists.mp4

11:10

8. Exploring Lists in Python.html

9. Functions.mp4

07:46

10. Find the Maximum.html

11. Basic String Manipulation.html

12. Even or Odd.html

13. Calculate the Factorial.html

14. Loops.mp4

08:05

15. Tuples.mp4

02:37

16. Sets.html

17. Find Unique Elements.html

18. Reverse a String.html

19. Calculate Sum of Digits.html

20. Check Palindrome.html

21. Fibonacci Series.html

22. Find the Nth Fibonacci Number.html

23. Check for Prime Numbers.html

24. Count Primes.html

25. Calculate Average.html

26. Count Occurrences in a List.html

27. Find the Missing Number.html

28. Find Common Elements in Two Lists.html

29. Remove Duplicates from a List.html

30. Count Occurrences of a Word.html

31. Check Balanced Parentheses.html

32. OOP Basics.mp4

07:44

33. Introduction to Object-Oriented Programming (OOP).html

34. Find the Maximum Class Edition.html

35. Implement a Stack.html

36. Implement a Queue.html

37. Find The Closest Number.html

38. Find the Longest Consecutive Subsequence.html

39. Merge Sorted Lists.html

40. Jupyter Notebook.mp4

07:23

41. Pandas Introduction.mp4

10:44

42. Data Manipulation.html

43. Interview Prep Data Manipulation (Hard).html

2. SQL and Databases

1. Install Postgres.mp4

05:03

2. Relational Database Management Systems (RDBMS).html

3.1 create users.zip

3. SQL Fundamentals.mp4

08:45

4. SELECT and WHERE.html

5. User Count Above 50.html

6. Order Analysis.html

7. Employee Database Query.html

8. Sales Analysis.html

9. WITH statement.html

10. Employee Salary Analysis.html

11. UNION and UNION ALL.html

12. Product Inventory Analysis.html

13. Customer Purchase Analysis.html

14. Order Analysis.html

15. Student Grades Analysis.html

16. Product Category Analysis.html

17. Order Date Analysis.html

18. NoSQL Databases.html

3. API Usage

1. What is an API.html

2. GET Request.html

3. POST Request.html

4. Postman.mp4

04:27

5. Extract Data.mp4

13:57

6. Interview Prep ETL.html

Description

From Novice to Data Engineer: Master Python and SQL for Data Processing

What You'll Learn?

Python Fundamentals
Variables, data types, and operators
Control flow (if statements, loops, etc...)
SQL Queries
Working with JSON and CSV data
Reading and writing files
Using libraries like requests to make HTTP requests
How to build functions and think like engineers
Data Cleaning and Transformation
Database Fundamentals (PostgreSQL)
Creating and managing databases and tables
Introduction to Postman
Testing RESTful APIs
Understanding what an API is
Retrieving data from an API

Who is this for?

Aspiring Data Engineers

Data Enthusiasts

Programming Novices

SQL Beginners

Career Switchers

Students and Recent Graduates

Business Analysts

Entrepreneurs and Start-up Founders

Self-Learners

Professionals Seeking Data Skills

What You Need to Know?

No prerequisites except high motivation!

More details

Description
Are you ready to embark on a journey into the world of data engineering? Welcome to "Data Engineering for Beginners with Python and SQL" â€“ the course that will empower you to build a strong foundation in data engineering, regardless of your prior experience.
In today's data-driven world, the demand for skilled data engineers is soaring, and this course is designed to help you seize the opportunities this field has to offer. Whether you're an aspiring data professional, a business analyst, or simply curious about the intricacies of data processing, this course is your gateway to acquiring the essential skills.
What You'll Learn:
SQL Mastery: Dive headfirst into SQL (Structured Query Language), the cornerstone of data management. You'll learn how to manipulate and query data effectively, ensuring you have a solid grasp of this fundamental skill.
Python: Explore the power of Python for data engineering and not only. We'll cover the basics and take you on a journey through Python possibilities.
ETL (Extract, Transform, Load) Processes: Gain insights into ETL processes, a critical component of data engineering. Discover how to efficiently extract data from various sources, transform it to meet your needs, and load it into target systems.
Course Highlights:
Materials and Exercises: This course focuses on practical learning. We believe in the "learn by doing" philosophy, so you'll find a wealth of materials and hands-on exercises to reinforce your knowledge.
Comprehensive Resources: Access a comprehensive collection of resources, including coding examples and reference materials to aid your learning journey.
Minimal Video, Maximum Learning: We understand the value of your time. While there will be instructional videos, engaging exercises and resources will be emphasized, allowing you to learn at your own pace.
Who this course is for:
Aspiring Data Engineers
Data Enthusiasts
Programming Novices
SQL Beginners
Career Switchers
Students and Recent Graduates
Business Analysts
Entrepreneurs and Start-up Founders
Self-Learners
Professionals Seeking Data Skills

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I specialize in designing, building, and maintaining scalable data pipelines that enable organizations to extract insights from their data. With a strong background in data architecture, database design, and ETL processes, I am well-versed in a variety of technologies and tools, including Spark, SQL, Azure, AWS, GCloud, and more.Throughout my career, I have successfully collaborated with cross-functional teams to develop data-driven solutions that support critical business initiatives. Whether it's optimizing data warehouses for faster query performance or automating data quality checks to ensure accuracy and completeness, I am committed to delivering high-quality, reliable data products that drive better decision-making.I am passionate about staying up-to-date with the latest trends and best practices in data engineering and enjoy sharing my knowledge through blog posts, conference talks, and mentorship. In my free time, I enjoy exploring new technologies and experimenting with personal projects that challenge me to expand my skills and knowledge.

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