AI and Machine Learning: Code, Train, & Deploy

Master the end-to-end lifecycle of artificial intelligence and machine learning in Skillspire's comprehensive, 16-week program. Designed to bridge theoretical foundations with rigorous technical execution, this course takes you from foundational Python programming and exploratory data analysis to building, training, and deploying advanced predictive models, neural networks, and modern generative AI tools.
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Your Instructor
Tesfay Aregay
A veteran of the "Big Tech" world, Tesfay has spearheaded critical infrastructure projects for Apple, Amazon, and Capital One. Currently serving as a Senior Engineer at Microsoft, he focuses on the resilience and stability of M365 global platforms. He leverages his 10+ years of expertise in distributed systems and AI-driven pipelines to mentor the next generation of engineers at Skillspire.
Course Overview

Master the end-to-end lifecycle of artificial intelligence and machine learning in Skillspire's comprehensive, 16-week program. Designed to bridge theoretical foundations with rigorous technical execution, this course takes you from foundational Python programming and exploratory data analysis to building, training, and deploying advanced predictive models, neural networks, and modern generative AI tools.

What you’ll learn

In this program, you will master the end-to-end data science and machine learning lifecycle, starting with essential Python and SQL foundations, data acquisition, and profiling for both structured and unstructured data using cloud platforms like Azure or Google Cloud. You will learn how to build, train, and evaluate classical and advanced predictive models—including Simple and Multiple Linear Regression, Logistic Regression, Decision Trees, Support Vector Machines (SVM), and Neural Networks—while exploring computer vision, natural language processing, and deep learning architectures. Additionally, you will integrate modern AI tools like ChatGPT and Blackbox.ai into your workflows, master model deployment strategies and cloud-based options, address AI ethics, and culminate your studies with an end-to-end real-world capstone project.

Course Objectives

Course Prerequisites

What does this course look like?

  • Skillspire’s AI and Machine Learning: Code, Train, & Deploy is an intensive, 16-week program meeting five times a week across 48 structured lessons. To ensure real-world readiness, the curriculum features regular pre-class assessments, practical lab assignments, and a rigorous final capstone project.
  • Who is it for?

    This course is designed for aspiring data scientists, programmers, and technical professionals looking to break into artificial intelligence or transition their skill sets toward building, training, and deploying advanced machine learning models. It is ideal for dedicated learners who are ready to commit to a rigorous 16-week schedule, engage in hands-on coding and cloud deployment workflows, and meet professional academic standards to launch a successful career in the AI-driven tech industry.

    Veterans and military spouses in Washington State may be eligible to use GI Bill® benefits or other VA education funding for the in-person program at Skillspire's SeaTac campus. The Washington Worker Retraining Program (WRT) may also provide funding for eligible students.

    Course Syllabus

    Course Program Stages
    Duration:
    Total Hours:
    Week
    Stage
    1
    -
    Introduction to Data Science and Review of Programming Fundamentals

    • Introduction to Data Science

    • Python Review

    • Variables and Data Types

    • Conditional Statements and Loops

    • Functions and Modules

    Week
    Stage
    2
    -
    Data Manipulation with Pandas

    • Introduction to Pandas

    • Loading Data with Pandas

    • Data Manipulation with Pandas

    • Aggregating and Grouping Data with Pandas

    • Data Cleaning and Preprocessing with Pandas

    Week
    Stage
    3
    -
    Working with Databases and APIs

    • Introduction to Databases

    • SQL Review

    • Introduction to APIs

    • Accessing Web APIs with Python

    • Processing JSON Data

    Week
    Stage
    4
    -
    Project 1 - Data Wrangling and Analysis

    • Working with a real-world dataset using Pandas and Python

    • Data Cleaning and Preprocessing

    • Exploratory Data Analysis

    Week
    Stage
    5
    -
    Review of Descriptives and Inferential Statistics

    • Descriptive Statistics

    • Probability Theory

    • Common Probability Distributions

    • Statistical Inference

    • Hypothesis Testing

    View the full program syllabus, click for access!

    Start Date
    June 17, 2026
    End Date
    October 12, 2026
    Enrollment Status
    Closed
    Location
    Remote
    Start Date
    June 17, 2026
    End Date
    October 12, 2026
    Enrollment Status
    Closed
    Location
    In-person
    Start Date
    March 11, 2026
    End Date
    July 2, 2026
    Enrollment Status
    Closed
    Location
    Remote

    Cohort Schedule

    Start Date
    End Date
    Enrollment Status
    Location
    No items found.
    Start Date
    June 17, 2026
    End Date
    October 12, 2026
    Enrollment Status
    Closed
    Location
    Remote
    Start Date
    June 17, 2026
    End Date
    October 12, 2026
    Enrollment Status
    Closed
    Location
    In-person
    Start Date
    March 11, 2026
    End Date
    July 2, 2026
    Enrollment Status
    Closed
    Location
    Remote

    Cohort Time Schedule

    Mon
    5:00PM - 8:00PM PST
    Tue
    5:00PM - 8:00PM PST
    Wed
    5:00PM - 8:00PM PST
    Thu
    5:00PM - 8:00PM PST
    Fri
    Sat
    9:00AM - 3:00PM PST
    Sun
    Start Date
    June 17, 2026
    End Date
    October 12, 2026
    Enrollment Status
    Closed
    Location
    Remote
    Start Date
    June 17, 2026
    End Date
    October 12, 2026
    Enrollment Status
    Closed
    Location
    In-person
    Start Date
    March 11, 2026
    End Date
    July 2, 2026
    Enrollment Status
    Closed
    Location
    Remote

    Want to learn full stack web development but don’t know where to start? Consider signing up to learn full stack with Python.

    Python is easy to learn and great for back-end coding. The popularity of Python as a programming language is on the upsurge, thanks to its readability and ability to do more with less coding. If you are looking for a course that offers Python web development for beginners, look no further. Our online course allows you to learn full stack web development with Python at your own pace from the comfort of your home.

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    As part of our full stack development course, you’ll also learn JavaScript and a suite of frameworks and tools that work with Java.

    Our Java full stack developer course is designed to kickstart your programming career as a Java full stack developer. We regularly update our Java full stack developer course to make sure it is relevant and useful for our students. If you want to join our full stack JavaScript course, but aren’t sure if you have time to attend the classes, don’t worry. We schedule our classes on weekends and weekday evenings. Even if you work full-time, you can still attend our classes.

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    2
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    3
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    The opportunity is yours. We help you take it.
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    Frequently asked questions
    Do I need programming experience for your courses?

    No, a basic level of computer literacy and a motivation to learn is all you need for most of our courses.

    Who should take your courses?

    Our courses are designed for diverse backgrounds; If programming or tech is a career track that you really want to pursue, you may sign-up for our courses whether you are software engineer, product/program manager, analyst, researcher, consultant, student, etc.

    How much time do I need to spend studying outside of the classroom?

    It can vary depending on your unique background. However, it usually takes 18 hours/week outside of the classroom for homework and study time.

    Will I be given a certificate after the completion of the course?

    Yes, you will be given a certificate of completion for any course, after you pass the final exam.