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LAUNCHING SOON.. IN OCTOBER 2024

Register below to be notified the moment our course content drops!  

Register your interest in this Google Form.  

Jump start your journey with Dataiku Cloud and Snowflake
Dataiku custom installation on a Linux server
Familiarizing yourself with Dataiku

 


COURSE CONTENT

Part 1: Getting started with Dataiku
Part 2: For Dataiku Admins
Part 3: Ingesting, Exploring and Preparing your Data
Part 4: LLMs and NLP
Part 5: Visual Machine Learning
Part 6: Computer Vision
Part 7: Dataiku for Coders
Part 8: ML Ops


 


PART 1: GETTING STARTED WITH DATAIKU

a. Jumpstart with Dataiku Cloud

 1. Jump start your journey with Dataiku Cloud and Snowflake

 2. Navigating the Launchpad



b. Navigating the UI as a Dataiku user 

 1. Familiarizing yourself with Dataiku

 2. Project Flow and Flow Panel

 3. Collaboration best practices: Project Documentation

 4. Collaboration best practices: Flow Zones, Tags, Discussions

 5. Project Security and sharing permissions


... (and more)



PART 2: FOR DATAIKU ADMINS

a. Self-Managed Dataiku: Setup & Configuration for Dataiku Admins

 1.  Dataiku custom installation on a Linux server

 2.  Upgrade Dataiku version on a Linux server

 3.  Setting up Dataiku to export documents, PDFs or images

 4.  Installing R Integration

 5.  Configuring Dataiku for SSL

 6.  Connecting to databases

 7.  Security and Permissions

 8.  High-level architecture (On-Premise)

 9.  Configuring of Automation and API node

 10. Configuring of GPUs -- target: December

 11. Connecting to external repositories -- target: December

 12. Monitoring of Dataiku using dkumonitor -- target: December

 13. High-level architecture (Cloud) -- target: December

 14. Deploy with Fleet Manager in AWS -- target: December

 15. Configuring kafka and working with streaming data -- target: December


... (and more)



PART 3: INGESTING, EXPLORING AND PREPARING YOUR DATA

a. Data Ingestion

 1. Methods to ingest data into your project


b. Data Exploration

 1. Concept Video: Understanding Sampling

 2. Analysis and Charts

 3. Interactive Statistics

 4. Deep Dive (Statistical Tests) -- target: December

 5. Deep Dive (Multivariate Analysis) -- target: December

 6. Deep Dive (Time Series Analysis) -- target: December


c. Data Preparation

 1. Using the Prepare Recipe for numerical data

 2. Using the Prepare Recipe for dates

 3. Using the Prepare Recipe for web log data

 4. Other useful Prepare Recipe tips

 5. Concept Video: Speed up your data processing by offloading compute


d. Data Transformations

 1. Join Recipe

 2. Aggregations

 3. Fuzzy Joins

 4. Concept Video: Making changes to the middle of your flow

 5. Auto feature generation -- target: November


... (and more)



PART 4: LLMS AND NLP

a. Natural Language Processing (NLP)

 1. Concept Video: Dataiku capabilities for NLP


b. Textual Data Preparation

 1. Using the Prepare Recipe for textual data

 2. Pre-processing textual data in AutoML


c. LLM Mesh

 1. Concept Video: LLM Mesh

 2. Setting up an LLM Connection

 3. Prompt Recipes and Prompt Studios

 4. Retrieval Augmented Generation (RAG)

 5. LLM Mesh API -- target: November

 6. Running local Hugging Face models -- target: November


... (and more)



PART 5: VISUAL MACHINE LEARNING

a. Introduction to Machine Learning

 1. Concept Video: Introduction to Machine learning and AutoML 

 2. Concept Video: Algorithm selection and hyperparameter tuning


b. AutoML Prediction (Supervised ML)

 1. Train and Tune a Prediction Model

 2. Interpret a Prediction Model's Results


c. Clustering (Unsupervised ML)

 1. Train a Clustering Model

 2. Interpret a Clustering Model's Results


d. Auto Time Series (AutoTS) Forecasting

 1. Train a AutoTS Forecasting Model

 2. Interpret a AutoTS Forecasting Model's Results


e. Causal Prediction

 1. Train a Causal Prediction Model

 2. Interpret a Causal Prediction Model's Results


f. Responsible AI

 1. Model Bias and Fairness


... (and more)



PART 6: COMPUTER VISION

a. Preparing your Data for Computer Vision -- target: December

 1. Working with Managed Folders

 2. Labeling your images


b. Computer Vision without Code -- target: December

 1. Concept Video: Deep Learning Model Architectures

 2. Performing Image Classification

 3. Performing Object Detection


... (and more)



PART 7: DATAIKU FOR CODERS

a. Working with Code in Dataiku  -- target: December

 1. Getting Started with Code Notebooks and Code Recipes

 2. Setting up a Code Environment

 3. Connecting to remote Git repository and importing code

 4. Code Libraries

 5. Variables

 6. Concept Video: Dataiku API

 7. Creating Custom Plugins


... (and more)



PART 8: ML OPS

a. Introduction to ML Ops

 1. Concept Video: What is MLOps?

 2. Concept Video: Understanding deployment options in Dataiku


b. Preparing for Deployment

 1. Setting up Scenarios

 2. Data Quality and Checks


c. Batch and Real-time API Deployment

 1. Batch deployment of projects and models via Bundles

 2. Concept Video: Real-time API services and endpoints

 3. Deploying, testing and enriching an API


d. Model Monitoring and Unified Monitoring

 1. Tracking data drift, model performance and metrics

 2. Unified Monitoring


... (and more)



Register your interest in this Google Form.  

We’ll notify you as soon as our course launches! In the meantime, you can tell
us which topics and languages you’d like us to prioritize.




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