Data Engineer — Proficient

Building upon the data engineering content already covered in the Starter and Intermediate Data Engineer training plans, the goal of this section is to strengthen your knowledge in order to equip you for the role.

We’ll take an in-depth look at machine learning, including model selection, supervised and unsupervised learning, regression, mathematics, and how to use Python for machine learning.

Next, we'll explore the world of data science and through a series of hands-on, practical tutorials, you'll learn how to use Python at an advanced level to process and analyze data.

You'll also get a comprehensive understanding of how to create, query, and manipulate data in relational databases using SQL, and go deep into transactions, subqueries, inline views, summarized queries, the exists predicate, and set operations.

After having completed this selection of content, you will be well equipped to carry out a wide variety of data engineering activities in both SQL and Python. Hit the Start Training Plan button below and take the next step towards your new career!

Average completion time (studying 3 hours a week)
68 working days
Content Duration
40h 31m
Data Engineer — Proficient
Content:
2
Exams
3
Learning Paths
Pre-Test: Data Engineer - Proficient
Pre-Test: Data Engineer - Proficient
Practical Machine Learning
Practical Machine Learning
Practical Data Science with Python
This learning path explores the world of data science and gives you hands-on, practical tutorials on how to use Python at an advanced level.
Working With SQL — Beyond the Basics
Practice using SQL to load and manipulate data with this learning path!
Post-Test: Data Engineer - Proficient
Post-Test: Data Engineer - Proficient