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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
Nov 18 - 19
09 AM - 05 PM (Europe/Paris)
English
$1500.00
Nov 18 - 19
10 AM - 06 PM (America/New_York)
English
$1500.00
Dec 05 - 06
09 AM - 05 PM (Europe/Paris)
English
$1500.00
Dec 11 - 12
09 AM - 05 PM (America/Los_Angeles)
English
$1500.00
Dec 16 - 19
09 AM - 01 PM (Asia/Kolkata)
English
$1500.00
Dec 16 - 19
02 PM - 06 PM (Europe/London)
English
$1500.00
Jan 06 - 07
09 AM - 05 PM (America/Chicago)
English
$1500.00
Jan 23 - 24
09 AM - 05 PM (Europe/Paris)
English
$1500.00
Jan 28 - 29
09 AM - 05 PM (Asia/Tokyo)
Japanese
$1500.00
Jan 28 - 29
09 AM - 05 PM (Europe/London)
English
$1500.00

Public Class Registration

If your company has purchased success credits or has a learning subscription, please fill out the Training Request form. Otherwise, you can register below.

Private Class Request

If your company is interested in private training, please submit a request.

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Registration options

Databricks has a delivery method for wherever you are on your learning journey

Runtime

Self-Paced

Custom-fit learning paths for data, analytics, and AI roles and career paths through on-demand videos

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Instructors

Instructor-Led

Public and private courses taught by expert instructors across half-day to two-day courses

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Learning

Blended Learning

Self-paced and weekly instructor-led sessions for every style of learner to optimize course completion and knowledge retention. Go to Subscriptions Catalog tab to purchase

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Scale

Skills@Scale

Comprehensive training offering for large scale customers that includes learning elements for every style of learning. Inquire with your account executive for details

Upcoming Public Classes

Generative AI Engineer

Generative AI Engineering with Databricks

This course is aimed at data scientists, machine learning engineers, and other data practitioners who want to build generative AI applications using the latest and most popular frameworks and Databricks capabilities. 

Below, we describe each of the four, four-hour modules included in this course.

Generative AI Solution Development: This is your introduction to contextual generative AI solutions using the retrieval-augmented generation (RAG) method. First, you’ll be introduced to RAG architecture and the significance of contextual information using Mosaic AI Playground. Next, we’ll show you how to prepare data for generative AI solutions and connect this process with building a RAG architecture. Finally, you’ll explore concepts related to context embedding, vectors, vector databases, and the utilization of Mosaic AI Vector Search.

Generative AI Application Development: Ready for information and practical experience in building advanced LLM applications using multi-stage reasoning LLM chains and agents? In this module, you'll first learn how to decompose a problem into its components and select the most suitable model for each step to enhance business use cases. Following this, we’ll show you how to construct a multi-stage reasoning chain utilizing LangChain and HuggingFace transformers. Finally, you’ll be introduced to agents and will design an autonomous agent using generative models on Databricks.

Generative AI Application Evaluation and Governance: This is your introduction to evaluating and governing generative AI systems. First, you’ll explore the meaning behind and motivation for building evaluation and governance/security systems. Next, we’ll connect evaluation and governance systems to the Databricks Data Intelligence Platform. Third, we’ll teach you about a variety of evaluation techniques for specific components and types of applications. Finally, the course will conclude with an analysis of evaluating entire AI systems with respect to performance and cost.

Generative AI Application Deployment and Monitoring: Ready to learn how to deploy, operationalize, and monitor generative deploying, operationalizing, and monitoring generative AI applications? This module will help you gain skills in the deployment of generative AI applications using tools like Model Serving. We’ll also cover how to operationalize generative AI applications following best practices and recommended architectures. Finally, we’ll discuss the idea of monitoring generative AI applications and their components using Lakehouse Monitoring.

Paid
16h
Lab
instructor-led
Associate

Questions?

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