PCDE Course Overview

DELETEME Test diff for deploy

Introduction

This is a course where MIT's xPro program will prepare you for a certification in the professional skills required in Data Engineering. The course will go through topics in Python programming, the basics of database design.

First Some Lessons About Good Note Taking

Interacting with Lectures

It's important to take notes on the content released each week. Good note taking can even save time on doing activities and assignments, as the information needed for some of them will often be within good notes taken.

Effective learning includes what goes on before lectures, during and after. The University of British Columbia have put together some recommendations on those three phases. Also there's another note on notetaking effectively, including the information presented in University of B.C.'s article.

Chat with your Learning Facilitators

There are times we're simply stumped, regardless of our best efforts. It's best to go through the modules as early as possible, with ample time to reach out to learning facilitators and peers. Attend office hours frequently, when possible, both for information reinforcement and to ask your questions. Submit support tickets to ask those questions and get extra guidance. You'll find instructions on how to submit support tickets in your Orientation Week Module.

Connect with your Fellow Learners

Just because you are viewing course material on your own, doesn't mean that you're the only one pursuing this certificate. Use Slack to connect with others, ask questions, and get some help from your peers. They may have the same difficulties as you or might have some great tips that will make the topics click.

The moral of the story here is that the more you can interact with course content in many ways, through effective note-taking, review and connecting with others, the more you'll be able to get the concepts down and get the most success from the course.

Some Time Management Recommendations

If taking the course in a well structured way, it should be taking about ~15 hours a week. This is a minimal recommendation and you may find yourself spending more than 20 hours per week some weeks. Integrating this time into your schedule will require disciplined time management. Here are some more in depth tips on managing time while in the program. Remember though with previous knowledge from previous cohort that is now deferred, shoot for 10 hours a week. If more time is necessary for each week it's important to seek help earlier.

Course Outline

Here is the outline copy: Here are the due dates for each module outlined

Career Guidance

Preparing a Data Engineering Portfolio

In this section, you will learn how to create a professional portfolio for the data engineering industry. This week, your learning facilitator will host the second in a series of mentorship workshops, designed to introduce you to the broader field of data engineering. The Industry Guidance mentorship workshop will discuss the following topics:

Here are some additional resources to supplement this module’s workshop focus:

After you have read through some of these resources, consider the following in your discussion post:

Module 0: Course Orientation

Notes Links

Key Activities

Module 1: Introduction to Python

Notes Links

Learning Outcomes

Key Activities

Module 2: Introduction to NumPy

Notes on Topic

Learning Outcomes

Module 3: Introduction to Pandas

Learning Outcomes

Note Links

Module 4: Databases & Intro to SQL

Module 5: Databases with SQL Statements

Notes on Topic

Key Activities

Outcomes

Module 6: Databases Analysis and the Client Server Interface

Notes on Topic

Key Activities

Time Log

Outcomes

Module 7: A Model to Predict Housing Prices

Due Date: 1629 UTC February 8, 2023 Available for late submission till: February 22, 2023

Notes on Topic

Key Activities

Outcomes

Module 8: ETL, Analysis, Visualization

Due Date: 4:29 PM UTC February 15, 2023 Available for late submission till: February 22, 2023

Notes on Topic

Key Activities

Outcomes

Module 9: GitHub & Advanced Python

Notes on Topic

Key Activities

Outcomes

Module 10: Networks

Outcomes

Notes on Topic

Module 11: Client Server Architecture

Note Links

Outcomes

In this module these topics will be covered:

The most difficult part of this section is correctly generating secure tokens for authentication, getting it wrong can mean loss of access to data or worse leaking data by an attacker.

Module 12: Types of Databases & Database Containerization

Due Data

Note Links

Outcomes

References

Web References

Notes Links