Start Learning AI With the ODSC West Data Primer Series Start Learning AI With the ODSC West Data Primer Series
The Data Primer series as part of the ODSC West Mini-Bootcamp Pass is your golden ticket to kickstarting your AI journey.... Start Learning AI With the ODSC West Data Primer Series

The Data Primer series as part of the ODSC West Mini-Bootcamp Pass is your golden ticket to kickstarting your AI journey. These live, virtual pre-bootcamp sessions, running from August to October, will get you ready to get the most out of your ODSC West conference experience this October 30th to November 2nd. Can’t attend them all live? You’ll also have access to the recordings on-demand. Check out the primer courses on learning AI below.

Data Primer

Available On-Demand

Data is the essential building block of data science, machine learning, and learning AI. This course is designed to teach you the foundational skills and knowledge required to understand, work with, and analyze data. It covers topics such as data collection, organization, profiling, and transformation as well as basic analysis. It will help you begin your AI journey and gain valuable insights that we will build up in subsequent SQL, programming, and AI courses:

Module 1: Module 2: Module 3: Module 4:
Introduction to Data Data Collection Data Transformation Data Analysis
  • What is Data
  • Why Data is Important
  • The Data Life Cycle
  • Understanding Data Types
  • Data-Centric AI
  • Data Collection
  • Sourcing Data
  • External Data
  • Licencing Data
  • Data Collection Tools
  • Data Transformation
  • Data Enrichment
  • Correlations and Outliers
  • Data Quality
  • Data Transformation Tools
  • Data Profiling
  • Describing a Dataset
  • Data Shaping and Shaping Examples
  • Data Analysis Tools

SQL Primer

Thursday, September 7th, 2023, 2 PM EST

This SQL coding course teaches students the basics of Structured Query Language, which is a standard programming language used for managing and manipulating data and an essential tool in learning AI. The course covers topics such as database design and normalization, data wrangling, aggregate functions, subqueries, and join operations. You will learn how to design and write SQL code to solve real-world problems. Upon completion, students will have a strong foundation in SQL and be able to use it effectively to extract insights from data.

Module 1: Module 2: Module 3: Module 4:
Data Wrangling Tables & Databases   SQL Syntax Data Manipulation
  • Introduction to Data Wrangling
  • Why SQL for Data Wrangling?
  • Data Lifecycle Review
  • SQL Data Types
  • Sourcing & Collecting Data
  • Data Storage
  • Popular Databases
  • Tables and Databases
  • Relational Data Design 
  • Data Normalization
  • Foreign and Primary Keys
  • Introduction to SQL Syntax
  • SQL Query Syntax
  • Understanding SQL CRUD (Create, Read, Update, Delete)
  • Filtering Data with SQL
  • Data Profiling with SQL
  • Subqueries in SQL
  • Loading and Inserting Data
  • Transaction Control  
  • Aggregate Functions and Groups
  • Join Operations
  • Updating Data with SQL

Programming Primer Course with Python

Thursday, September 21st, 2023, 2 PM EST

The Python language is one of the most popular programming languages in data science and machine learning as it offers a number of powerful and accessible libraries and frameworks specifically designed for these fields. This learning AI programming course is designed to give participants a quick introduction to the basics of coding using the Python language.

It covers topics such as data structures, control structures, functions, modules, and file handling. This course aims to provide a basic foundation in Python and help participants develop the skills needed to progress in the field of data science and machine learning.

Module 1: Module 2: Module 3: Module 4:
Introduction Data Structures Functions and modules OOP & Libraries
  • Introduction 
  • Basic concepts
  • Variables & data types
  • Operators
  • Control structures,
  • Functions
  • Data Structures
  • Arrays
  • Lists
  • Tuples
  • Dictionaries
  • Manipulating structures
  • Defining functions
  • Calling functions
  • Passing & returning values
  • Built-in functions
  • Importing modules.
  • File I/O
  • Object-oriented programming
  • Defining classes and objects
  • Inheritance
  • Exception handling
  • External libraries

AI Primer Course

Thursday, October 5th, 2023, 2 PM EST

Data wrangling is the cornerstone of any data-driven project, and Python stands as one of the most powerful tools in this domain. This course offers attendees a hands-on experience to master the essential techniques of data wrangling. From cleaning and transforming raw data to making it ready for analysis, this course will equip you with the skills needed to handle real-world data challenges.

Upon completion of this short learning AI course, attendees will be fully equipped with the knowledge and skills to manage the data lifecycle and turn raw data into actionable insights, setting the stage for advanced data analysis and AI applications.

Module 1: Module 2: Module 3: Module 4:
Introduction Data Cleaning Data Transformation Data Manipulation
  • Introduction to Data Wrangling
  • Importance and role of data wrangling in the data analysis process
  • Overview of data cleaning, transformation, and reshaping
  • Data sources
  • Techniques for obtaining data
  • Handling missing data
  • Dealing with outliers and duplicates
  • Addressing data quality issues
  • Reshaping data
  • Pivoting, melting, and stacking
  • Handling categorical variables
  • Converting between data types
  • Normalization and scaling
  • The Pandas Library
  • Filtering, sorting, and aggregating data
  • Data Integration and Joining
  • Combining data  
  • Merging and joining datasets

Data Wrangling with Python Course

Thursday, October 19th, 2023, 2 PM EST

This AI literacy course is designed to introduce participants to the basics of artificial intelligence (AI) and machine learning.You will first explore the various types of AI and then progress to understand fundamental concepts such as algorithms, features, and models. You will study the machine learning workflow and how it is used to design, build, and deploy models that can learn from data to make predictions. This will cover model training and types of machine learning including supervised, and unsupervised learning, as well as some of the most common models such as regression and k-means clustering.

Upon completion, individuals will have a foundational understanding of machine learning and its capabilities and be well-positioned to take advantage of introductory-level hands-on training in machine learning and data science.

Module 1: Module 2: Module 3: Module 4:
Introduction Types of ML Supervised Learning Unsupervised Learning
  • An Overview of AI
  • The AI Stack
  • Machine Learning Definitions
  • ML vs Traditional Programming
  • Algorithms and Models
  • Machine Learning Workflow
  • Independent vs Dependent Variables
  • Feature Selection
  • Data Labeling
  • Training & Testing Models
  • Structured and Unstructured Data
  • Types of Machine Learning
  • Supervised Machine Learning
  • Popular ML Algorithms
  • Classification Models
  • Regression Models
  • Which Model to Use?
  • Feature Extraction
  • Unsupervised Machine Learning
  • Supervised vs Unsupervised ML
  • K-Means Cluster Models
  • Deep Learning Overview 
  • Deep Learning vs Machine Learning

LLMs, Prompt Engineering, and Generative AI

Coming Fall 2023

In the rapidly evolving field of AI, the “LLMs, Prompt Engineering, and Generative AI” course stands as a cutting-edge offering, designed to equip learners with the latest advancements in Large Language Models (LLMs), prompt engineering, and generative AI techniques. This course delves into the architecture and functioning of LLMs, the art of crafting effective prompts to guide AI responses, and the principles behind generating creative and coherent content. As these components are becoming integral to the AI stack, understanding them is essential for anyone looking to innovate, optimize, and excel in AI-driven applications.

Whether you’re a researcher, developer, or AI enthusiast, this course will provide you with the insights and hands-on experience needed to harness the power of these transformative technologies and stay at the forefront of the AI revolution.

Module 1: Module 2: Module 3: Module 4:
LLM Basics Prompt Engineering ChatGPT API  Fine Tuning LLMs
  • Large Language Models (LLMs)
  • Transformer architecture
  • Applications of LLMs
  • Using LLMs out of the box
  • The process flow of chaining
  • Text summarization
  • Question answering
  • Text similarity
  • Fundamentals
  • Prompt engineering examples
  • Manipulation prompt
  • Prompt engineering guardrails
  • Impact responses from prompting
  • Temperature – predictable versus creative outputs
  • Tokens & Prompting
  • Iterative Prompt Development
  • Evaluate OF prompt effectiveness
  • Guiding model behavior
  • Build your own Chatbot
  • Common shortfall of prompting
  • Hallucinations, Fairness, Biases, & Jailbreaking
  • Fine-tuning introduction
  • When to fine-tune
  • Model stages
  • Classification
  • Topic Modeling, Sentiment analysis, and Entity recognition examples
  • Pre-training
  • Hardware and data considerations

Start Learning Today!

You may feel too old for school, but you’re never too old to learn. In this learning season, get your ODSC West Mini-Bootcamp pass and build new job-ready skills, gain new knowledge, and make new connections. Register now–50% off all in-person and virtual passes.




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