Databricks ML Essentials

This course empowers training companies and sales professionals to confidently sell and deliver Instructor-Led Training (ILT) on Databricks Machine Learning (ML). Combining technical mastery with sales strategies, participants will learn to position Databricks ML solutions effectively, manage data workflows using Delta tables, leverage tools like AutoML and MLflow, and demonstrate the business value of ML applications. Tailored for the high-tech sector, this program equips teams with the skills to address client needs, showcase ROI, and deliver impactful training experiences.
  • SKU:
    MLBD-2D-ILT-101
$80.00
$80.00 $100.00
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Databricks ML Essentials

Short Description

Designed specifically for training companies and sales professionals in the high-tech sector, this comprehensive course equips your team with the skills and knowledge needed to sell and deliver Databricks Machine Learning (ML) solutions through Instructor-Led Training (ILT). This program provides a seamless blend of technical understanding and sales strategies, enabling participants to confidently position Databricks ML training to corporate clients and drive business growth.

Key Features:

  • Master Databricks ML Fundamentals:

    • Understand the Databricks Lakehouse architecture and Medallion design for data engineering and ML workflows.
    • Learn to manage data efficiently using Delta tables and develop robust pipelines for machine learning applications.
    • Explore AutoML and MLflow for building, training, and deploying ML models effectively.

  • Practical Insights into ML Applications:

    • Discover advanced tools for embedding and managing large datasets in real-time environments.
    • Leverage Retrieval-Augmented Generation (RAG) systems for AI-driven business problem-solving.
    • Create impactful visualizations and dashboards to showcase ML capabilities and outcomes.

  • Sales-Driven Training Enablement:

    • Develop strategies to position and sell Instructor-Led Training for Databricks ML to corporate clients.
    • Address client pain points by demonstrating the ROI and business value of Databricks ML.
    • Tailor training solutions to align with diverse customer needs in high-tech environments.

Who Should Attend:

  • Training organizations aiming to expand their high-tech course offerings with Databricks ML.
  • Sales professionals seeking to enhance their ability to sell Instructor-Led Training in technical domains.
  • Trainers and instructors looking to deliver impactful Databricks ML training programs.

Why Choose This Course:

  • Built on proven methods and insights from Databricks ML in Action.
  • Designed to combine technical mastery with sales enablement for training companies.
  • Focused on practical, real-world applications to help clients achieve measurable success.

Equip your team with the expertise to deliver compelling Databricks ML training solutions that meet the needs of high-tech clients and position your organization as a leader in the industry.

Course Outline

Day 1: Foundations of Databricks Machine Learning

Agenda

  • Introduction to Machine Learning concepts and practical applications in business.
  • Overview of the Databricks Lakehouse platform and its role in unified analytics.
  • Managing data workflows with Delta Lake: time travel, versioning, and optimization.
  • Data preparation techniques: cleaning, feature engineering, and handling missing values.
  • Exploratory data analysis: leveraging visualizations to uncover trends and anomalies.
  • Developing basic machine learning models: examples in regression and classification.
  • Evaluation metrics: understanding accuracy, precision, recall, F1 score, and addressing overfitting challenges.

Learning Objectives

  • Understand the fundamentals of machine learning and Databricks architecture.
  • Learn to clean, prepare, and explore data for machine learning workflows.
  • Build and evaluate basic machine learning models using appropriate metrics.

Day 2: Advanced Applications and Deployment

Agenda

  • Advanced machine learning techniques: ensemble methods (e.g., random forests, gradient boosting) and neural networks.
  • Hyperparameter tuning: grid search, random search, and optimization tools.
  • Databricks AutoML: automating model creation and refining workflows.
  • Model deployment strategies: batch processing, real-time predictions, and scalability considerations.
  • Managing machine learning models with MLflow: tracking, versioning, and deployment best practices.
  • Monitoring deployed models: ensuring ongoing performance and reliability.
  • Ethical considerations: addressing bias, ensuring fairness, and maintaining ethical AI practices.
  • Future trends in ML: exploration of innovations like Retrieval-Augmented Generation (RAG) and reinforcement learning.

Learning Objectives

  • Apply advanced techniques to improve model performance and reliability.
  • Utilize Databricks AutoML and MLflow for streamlined workflows and deployment.
  • Deploy and monitor machine learning models using best practices for real-world applications.
  • Understand ethical considerations and future trends shaping the ML landscape.
What's Included

Instructor Kit

(PPTX/PDF of Slides + Optional Instructor Notes)
Comprehensive slide deck with detailed content covering all modules, plus optional instructor notes to enhance teaching effectiveness.

Student Kit / Handout

(with Free Branding)
Professionally designed handouts for students, including all essential course information and customizable branding options for your organization.

Course Agenda / Outline

Detailed day-by-day course agenda and outline, ensuring smooth course delivery and a structured learning experience for students.

Study Guide

A concise guide summarizing key concepts and topics covered in the course, perfect for post-course review and exam preparation.

FAQ

Answers to commonly asked questions about the course content, delivery, and labs to support instructors and students.

Briefing Doc

A high-level document summarizing the course objectives, target audience, and key learning outcomes, ideal for internal use and marketing.

Sales Enablement Kit for IT Training Sales Engineers

(Additional Fee)
Exclusive toolkit designed for IT training sales teams, including pitch decks, objection handling, and ROI documentation to support course sales.

Course AI GPT

(Course Assistant GPT so students can talk to the course materials!)
A cutting-edge AI-driven assistant that allows students to interact with course content, ask questions, and receive instant feedback.

Optional Podcast

(of the entire course or for each individual module)
Engaging audio content covering the entire course or individual modules, perfect for on-the-go learning or reinforcement.

Lab Guide

(Lab Environments are additional and can be found at CourseLabs.io)
Step-by-step lab guide to support hands-on learning, with lab environments available separately at CourseLabs.io.

Lab Files

(If you choose to host your own lab environment)
All necessary files and instructions for setting up and running labs in your own environment, offering flexibility in deployment.

Software Version

Databricks AutoML: Automated machine learning workflows (latest stable version).

MLflow: Manage ML lifecycle, including tracking and deployment (latest stable version).

Apache Spark: Distributed computing engine (latest stable version).

Delta Lake: Reliable and optimized data storage layer (latest stable version).

Databricks SQL (DBSQL): SQL interface for querying and visualization (latest stable version).

Databricks Lakehouse Monitoring: Monitoring and alerting for models and data (latest stable version).

Python Libraries: Scikit-learn, XGBoost, Keras, and others (latest stable versions).

More Information

Why Choose This Course?
The Databricks ML in Action course is the ultimate solution for professionals and organizations seeking to master Databricks Machine Learning tools. This comprehensive program blends technical knowledge with practical applications, providing the perfect balance of 50% lecture and 50% hands-on labs to ensure real-world success.

Course Objectives

  • Gain a deep understanding of the Databricks Lakehouse architecture and ML tools.
  • Learn to build and manage machine learning pipelines using Delta Lake, AutoML, and MLflow.
  • Develop practical skills for deploying ML models and interpreting insights.
  • Create impactful dashboards and visualizations to showcase ML outcomes.

Learning Objectives

At the end of the course, participants will:

  • Be confident in building, training, and deploying ML models on Databricks.
  • Master the use of Databricks tools for data preparation and real-time analytics.
  • Apply their knowledge to solve real-world business problems with ML.

Who This Course is For

This course is designed for:

  • Data Scientists and ML Engineers looking to enhance their expertise with Databricks.
  • Data Engineers aiming to streamline workflows and optimize performance.
  • Business Analysts seeking to leverage ML insights for better decision-making.
  • Technical Trainers delivering impactful Databricks ML training programs.

Flexible Course Options

We offer customizable training to meet the unique needs of your organization:

  • Available Formats: 1, 2, 3, 4, or 5-day courses.
  • Pricing: $40 per student, per day.
  • Tailored courseware to fit your team’s specific goals and challenges.

Empower your team with the knowledge and tools they need to excel in Databricks Machine Learning. Contact us today to customize your training experience!

Refund Policy

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We want you to be 100% satisfied with your purchase. Items can be returned or exchanged within 30 days of delivery.