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Introduction to Python for Data Science and Data Engineering

This course is intended for complete beginners to Python to provide the basics of programmatically interacting with data. The course begins with a basic introduction to programming expressions, variables, and data types. It then progresses into conditional and control statements followed by an introduction to methods and functions. You will learn the basics of data structures, classes, and various string and utility functions. Lastly, you will gain experience using the pandas library for data analysis and visualization as well as the fundamentals of cloud computing. Throughout the course, you will gain hands-on practice through lab exercises with additional resources to deepen your knowledge of programming after the class.

Skill Level
Associate
Duration
12h
Prerequisites

None

Outline

Day 1

  • Introduction to the Databricks environment

  • Python overview

  • Variables and data types

  • Complex data types

  • Control flow

  • Loops

  • Functions

  • Classes


Day 2

  • Using libraries

  • Data analysis with pandas

  • Advanced methods in Pandas

  • Data visualization

  • Cloud computing 101

  • Capstone and next steps 

Upcoming Public Classes

Date
Time
Language
Price
May 07
09 AM - 01 PM (America/New_York)
English
$1500.00
May 20
09 AM - 01 PM (Europe/London)
English
$1500.00
Jun 04
02 PM - 06 PM (America/New_York)
English
$1500.00
Jun 19
09 AM - 05 PM (Asia/Tokyo)
Japanese
$1500.00
Aug 21
09 AM - 05 PM (America/New_York)
English
$1500.00

Public Class Registration

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Upcoming Public Classes

Data Engineer

Data Workloads with Repos and Workflows

Moving a data pipeline to production means more than just confirming that code and data are working as expected. By scheduling tasks with Databricks Jobs, applications can be run automatically to keep tables in the Lakehouse fresh. Using Databricks SQL to schedule updates to queries and dashboards allows quick insights using the newest data. In this course, students will be introduced to task orchestration using the Databricks Workflow Jobs UI. Optionally, they will configure and schedule dashboards and alerts to reflect updates to production data pipelines. Learning objectives Version code with Databricks ReposOrchestrate tasks with Databricks Workflow Jobs. Use Databricks SQL for on-demand queries. Configure and schedule dashboards and alerts to reflect updates to production data pipelines.Prerequisites Ability to perform basic code development tasks using the Databricks Data Engineering & Data Science workspace (create clusters, run code in notebooks, use basic notebook operations, import repos from git, etc) Ability to configure and run data pipelines using the Delta Live Tables UI. Beginner experience defining Delta Live Tables (DLT) pipelines using PySpark Ingest and process data using Auto Loader and PySpark syntax. Process Change Data Capture feeds with APPLY CHANGES INTO syntax Review pipeline event logs and results to troubleshoot DLT syntax Reshape and manipulate complex data using advanced built-in functions. Production experience working with data warehouses and data lakes. Last course update April 2023
Paid
4h
Lab
instructor-led
Associate
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March 20

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Questions?

If you have any questions, please refer to our Frequently Asked Questions page.