Course Objectives

By the end of this class students will be able to:

• Define “Machine Learning” and differentiate it from other kinds of “Artificial Intelligence”

• Describe and differentiate between the three main types of Machine Learning:

• Supervised Learning

• Unsupervised Learning

• Reinforcement Learning
  

• Identify and distinguish between common “task types” for ML systems, specifically:

• Clustering

• Regression

• Classification

• Generation
  

• Describe various strengths and weaknesses of ML.

• Define the stages of the “Machine Learning Software Lifecycle”

• Perform data analysis and transformation workloads in Python with Pandas.

• Build, train, and evaluate several ML models including:

• Linear and Logistic Regression

• Decision Trees

• Neural Networks

And, depending on specializations:

• Deploy ML models to simple web servers.

• Build advanced model types for working with structured data, specifically:

• Random Forests

• Gradient Boosted Machines

• Build advanced types of neural networks, specifically:

• Convolutional Neural Networks for Computer Vision

• Generative Adversarial Networks for Image Generation

• Recurrent Neural Networks for NLP tasks

Prerequisites

• Beginner to Intermediate level Python.

• Comfortable with math.

• Bonus points for specific familiarity with:

• The derivative from calculus.

• High school level statistics.

• Multidimensional spaces (linear algebra).

Classroom Experience

Teb’s Lab courses have an emphasis on hands-on education. This class is organized around a repeated 3-step pattern:

First, your instructor will provide a walkthrough of a snippet of Python code. This will involve line by line analysis of the code, use of a debugger to examine the state of the code after each line executes, and “micro-exercises” to allow students to test their understanding and apply the new concepts.

Second, students will tackle a longer exercise. These exercises will challenge students to apply the concepts and — as the course progresses — combine new knowledge with previously acquired skills. During these exercises students will receive direct support and feedback from the instructor.

Third, students will see and share solutions to the exercise. One solution will be provided by the instructor. Additionally, students will be invited to share their own solutions. Those who do will receive the gift of additional feedback from their peers and the instructor. Those who do not will still have the opportunity to give feedback, and learn from their peers’ work.

Courses with Teb’s Lab are keenly focused on a class atmosphere that is:

• Interactive and challenging; wrestling with tough concepts is a cornerstone of learning.

• Welcoming and inclusive; safety and comfort allow learners to be present and engaged.

• Fun and interesting; boredom is the bane of education. 

Logistics and Pricing

• Teb’s Lab classes are delivered over Zoom.

• We charge a flat rate of $600 per classroom hour.

• With a full class of 20 students this is only $30 per student per hour.

• This class is capped at 20 students per session.

How To Book This Class

Use the form below to schedule a free consultation regarding this course. We do not book any courses without a consultation to ensure alignment on course goals and delivery logistics.