Data Science

Machine Learning and AI Foundation

GROUP TRAINING

Overview

Learn to take your solutions to the next level by harnessing the power of data in Machine Learning Foundation, a 3-day instructor-led course tailored for tech professionals. This comprehensive program covers essential topics, including the principles of machine learning, model development and evaluation strategies, as well as techniques for processing and understanding data. Gain hands-on experience with machine learning toolkits such as PyTorch, Scikit-Learn, Polars, NumPy and Plotly. Prerequisites include intermediate programming skills, mathematics foundation, data analysis familiarity, and a willingness to review pre-course materials. Elevate your skills and analyze data and build machine learning solutions. Enroll today to advance your career and stay competitive in the ever-evolving field of Machine Learning.

Duration

3 Days

Who Should Take This Course

Audience

Developers, Data Engineers, IT and QA Staff, Technical Managers, DevOps Engineers, Analysts, Project Managers.

Prerequisites

Participants should have beginner programming skills (preferably in Python), a foundational understanding of mathematics and statistics, experience with data analysis using tools like Pandas, a grasp of computer science fundamentals, familiarity with common operating systems and basic command-line operations, and a willingness to review pre-course materials.

These prerequisites will help participants engage effectively with the course material and hands-on labs, making the learning experience more rewarding. Attendees will also need to be able to ssh into a supplied cloud instance during the course to complete the lab work.

Why You Should Take This Course

Upon completing this course, participants will be able to:

Understand the fundamental concepts of machine learning and how they’re applied to provide value
Learn how to develop, tune and test machine learning models
Become familiar with tools for machine learning and data analysis
Gain insight into how production grade machine learning solutions are developed
Acquire hands-on experience building models and solving problems with ML
Learn insights from industry veterans about how to develop successful ML projects
Develop the skills and understanding to develop deep learning solutions

Course Outline

Machine Learning and AI Foundation

Day 1: Fundamentals

1. Machine Learning Overview
2. Data Processing with NumPy and Pandas
3. Data Preparation
4. Data Visualization and Exploratory Data Analysis

Day 2: Machine Learning Models

1. Measuring Models – Losses and Metrics
2. Linear Models
3. Nonlinear Models: Supervised
4. Nonlinear Models: Unsupervised

Day 3: Deep Learning

1. Hyperparameter Tuning and Experimentation
2. Deep Learning Fundamentals
3. Training Neural Networks
4. Building Deep Learning Models with PyTorch