• Admission Date

    Announcing Soon

  • Program Duration

    6 months (8-10 hrs/week)

  • Learning Format

    Live, Online, Interactive

Why Join this Program

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    UCSB PaCE Edge

    Earn a program completion certificate from UCSB PaCE and Simplilearn.

    Earn a program completion certificate from UCSB PaCE and Simplilearn.

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    Hands-On Learning

    Work on 14+ industry projects, including 3 capstones across different industry domains.

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    In-Demand AI Tools

    Explore 30+ modern AI tools, including Keras, PyTorch, Hugging Face, Docker & more.

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    1 Program. Full ML Lifecycle

    Learn from data preparation and model building to deployment.

Corporate Training

Enroll your employees into this program, NOW!

Program Overview

This 6-month online certificate program in AI builds practical skills in machine learning, deep learning, GenAI, and MLOps. Through live online classes and applied projects, learners explore, design, develop, and deploy AI models and explore modern GenAI and Agentic AI frameworks.

Key Features

  • Earn a program completion certificate from UC Santa Barbara Professional and Continuing Education and Simplilearn
  • Attend live, online interactive classes delivered by industry experts
  • Program curriculum approved by UCSB PaCE to ensure academic rigor and real-world relevance
  • Engage in a 6-month learning experience through live online classes with the flexibility to revisit class recordings at your convenience
  • Gain hands-on experience with 14+ real-world projects, including 3 capstone projects and 130+ demos and exercises
  • Explore 30+ cutting-edge AI tools across AI/ML lifecycle, from basics to deployment
  • Develop proficiency in 10+ skills, including machine learning, deep learning, LLMs, generative AI, agentic AI, and more
  • Implement MLOps practices to manage the machine learning lifecycle, including model deployment, monitoring, and retraining
  • Explore modern AI frameworks and agent-based AI systems used in real-world applications
  • Receive Microsoft certificates upon completing Microsoft-aligned AI courses on the Microsoft Learn
  • Explore modern AI frameworks and agent-based AI systems used in real-world applications
  • Understand how to build generative AI applications using large language models
  • Simplilearn Career Service helps you get noticed by top hiring companies
  • Attend a masterclass delivered by industry expert on Agentic AI

Post Graduate Program Advantage

The program curriculum is approved by UCSB PaCE to ensure academic rigor and real-world relevance. Through projects, capstone, demos & exercises, learners will build practical skills to stay ahead in their AI careers.

  • Program Certificate

    Certificate 1

    • Earn a program completion certificate from UCSB PaCE and Simplilearn
    • Learn through a curriculum approved by UCSB PaCE to ensure academic rigor and relevance
  • Industry Certificate

    Certificate 2

    • Earn Microsoft Learn certificate for Microsoft-aligned AI course
    • Gain exposure to Microsoft AI tools

Program Details

The learning journey combines online live classes, hands-on projects, and exploration of AI tools. Learners progress through courses covering data science, machine learning, deep learning, generative AI, and MLOps before completing a capstone project.

Learning Path

  • UCSB AIML: Program Induction
    • Introduction to the program structure and curriculum
    • Overview of learning journey and expected outcomes
    • Understanding the support system available to learners
    • Key concepts and skills covered throughout the program
  • UCSB AIML: Python Refresher with AI
    • Programming Foundations and Python Development Environment
    • Python Basics: Syntax, Variables, Data Types, Operators
    • Data Structures: Lists, Tuples, Dictionaries, Sets
    • Conditional Statements, Loops, and Comprehensions
    • Functions and Object-Oriented Programming
    • File Handling and Error Handling in Python
    • AI-Powered Code Generation and GitHub Copilot
    • Prompting and Debugging AI-Generated Code
  • UCSB AIML: Applied Data Science with Python
    • Introduction to Data Science
    • Python Programming Essentials
    • NumPy Fundamentals
    • Linear Algebra
    • Math and Statistics Foundations
    • Probability Distributions
    • Advanced Statistics
    • Working With Pandas
    • Data Analysis, Wrangling, and Visualization
    • End-to-End Statistics Applications in Python
  • UCSB AIML: Machine Learning
    • Introduction to Machine Learning
    • Supervised Learning: Regression and Applications
    • Supervised Learning: Classification and Applications
    • Ensemble Learning Techniques
    • Unsupervised Learning: Clustering, Dimensionality Reduction, Anomaly Detection
    • Recommendation Systems
  • UCSB AIML: Deep Learning Specialization
    • Introduction to Deep Learning
    • Artificial Neural Networks and Deep Neural Networks
    • TensorFlow and PyTorch
    • Model Optimization and Performance Improvement
    • Convolutional Neural Networks
    • Transfer Learning
    • Object Detection
    • Recurrent Neural Networks
    • Transformer Models for NLP
    • Autoencoders
  • UCSB AIML: GenAI Literacy
    • Introduction to Generative AI and Applications
    • GenAI Tools and Open-Source Ecosystem
    • Prompt Engineering Fundamentals
    • Introduction to Security, Bias, and Responsible AI Use
    • Emerging Trends in AI
    • Hands-On With ChatGPT and Multimodal AI
    • Exploring Custom GPTs and AI Assistants
    • Generative AI in Business Applications
  • UCSB AIML: Advanced Generative AI
    • Foundations of Advanced Generative AI Models and Architectures
    • Variational Autoencoders (VAEs) and Generative Adversarial Networks (GANs)
    • Transformers and Attention Mechanisms
    • Self-Attention and Multi-Head Attention in Modern AI Models
    • Building and Evaluating Generative AI Applications
    • LLM Fine-Tuning and Optimizing Generative AI Models
    • Applications of Advanced Generative AI Across Industries
    • Emerging Techniques and Future Developments in Generative AI
  • UCSB AIML: MLOps
    • Introduction to MLOps and the ML Lifecycle
    • Model Development and Experiment Tracking
    • Data and Model Versioning
    • Building ML Pipelines
    • Model Deployment and Production Serving
    • Model Monitoring and Drift Detection
    • Automating ML Workflows and CI/CD
    • Scaling ML Systems on Cloud Platforms
  • UCSB AIML: Capstone Project
    • Concludes with a capstone project applying skills across Python, data science, machine learning, deep learning, and generative AI
    • Work on real-world projects such as vehicle detection or retail sales forecasting
    • Receive guidance from an industry expert to complete the capstone
    • Develop a portfolio-ready project demonstrating job-ready AI skills
Electives:
  • UCSB AIML: End-to-end machine learning operations (MLOps) with Azure Machine Learning
    • Introduction to practical implementation of MLOps using modern cloud tools
    • Learn to automate ML workflows and manage experiments effectively
    • Understand integration of version control, testing, and continuous integration
    • Explore the use of Azure Machine Learning and GitHub Actions
    • Gain exposure to end-to-end ML lifecycle, from experimentation to production
  • UCSB AIML: Git and GitHub for AI & ML Professionals
    • Develop version control skills for collaborative development using Git and GitHub
    • Understand version control systems, the Git lifecycle, and key repository management commands
    • Learn core Git operations, including push, pull, fork, and pull requests
    • Explore branching, merging, and conflict resolution techniques
    • Introduction to GitHub Actions for automating CI/CD workflows
    • Understand triggers, job dependencies, and workflow configuration for automation
  • UCSB AIML: Masterclass on Agentic AI
    • Introduction to agentic AI systems and intelligent agents
    • Understand how agents plan, reason, and act autonomously or semi-autonomously
    • Explore how agents manage complex tasks with minimal human input
    • Learn how agentic systems function across real-world workflows
    • Understand the role of agentic AI in enabling automation
    • Gain insights into building efficient AI-driven solutions
  • UCSB AIML: Develop AI agents on Azure
    • Introduction to developing AI agents using Microsoft Azure and Azure AI Foundry
    • Understand how AI agents work and when to use them
    • Gain exposure to building, testing, and deploying AI agents using modern tools and frameworks
    • Explore extending agents with custom tools and capabilities
    • Understand how to design multi-agent solutions for complex use cases
    • Gain exposure to building workflows that integrate enterprise knowledge to complete tasks efficiently
  • UCSB AIML: Agentic AI Frameworks with Model Context and Tooling Protocols
    • Introduction to the architecture and design of modern AI agents
    • Understand how LLM agents perceive, reason, and act across workflows
    • Explore frameworks such as LangGraph, AutoGen, and CrewAI
    • Learn about the Model Context Protocol (MCP) and its role in agent systems
    • Understand how AI systems securely interact with external tools and data sources
    • Gain exposure to building collaborative AI applications

Contact Us

1-844-532-7688

(Toll Free)

12+ Skills Covered

  • Agentic AI
  • MLOps
  • Machine Learning
  • Deep Learning
  • ML Model Training
  • ML Model Optimization
  • ML Model Evaluation
  • ML Model Validation
  • Model Deployment
  • Generative AI
  • LLMs
  • Statistics

30+ Tools Covered

AIML_PythonAIML_Google ColabAIML_PandasAIML_NumPyAIML_SciKitAIML_MatplotlibAIML_SeabornAIML_SciPyAIML_SymPyAIML_TensorFlowAIML_PytorchAIML_KerasAIM_OpenCVAIML_ChromaAIM_ChatGPTAIML_GradioAIML_Hugging FaceAIML_Dall-E 2AIML_LangChainAIML_DockerAIML_DVCAIML_FastAPIAIML_GitMS-AGI-Github-CopilotAIML_MLflowAIML_TerraformAIM_SagemakerMS-AGI-CrewAIMS-AGI-LangGraphMS-AGI-AutoGen

Industry Projects

  • Project 1

    Autonomous Driving

    Build a deep learning model to classify and localize vehicles in images and analyze autopilot usage and its impact on road safety.

  • Project 2

    Enhancing Tourism With AI

    Develop an AI model that categorizes historical structures using image data and builds a recommendation engine to guide tourists to places of interest.

  • Project 3

    MLOps Lifecycle

    Implement an end-to-end MLOps pipeline including model training, versioning, deployment, and monitoring to manage the machine learning lifecycle.

  • Project 4

    Creating Cohorts of Songs

    Perform exploratory data analysis and clustering to group songs into cohorts and identify patterns that define similarities between them.

  • Project 5

    Lending Club Loan Data Analysis

    Explore and transform lending club datasets to develop predictive models that estimate loan default probabilities and improve credit evaluation.

  • Project 6

    Building a Python Adventure Game With GitHub Copilot

    Build a text-based adventure game using Python while leveraging GitHub Copilot to assist with coding, logic development, and debugging.

  • Project 7

    Marketing Campaigns

    Perform exploratory data analysis and hypothesis testing on marketing campaign data to measure campaign effectiveness and identify improvement opportunities.

  • Project 8

    Crafting an AI Powered HR Assistant

    Develop a conversational AI assistant capable of answering HR-related queries by leveraging generative AI and natural language processing techniques.

  • Project 9

    Analyzing Customer Orders Using Python

    Analyze customer order data to structure, store, and manipulate information using Python and generate meaningful business insights from transactional datasets

  • Project 10

    Sales Analysis

    Analyze company sales data using exploratory data analysis to uncover trends, patterns, and insights that can support business decision-making.

  • Project 11

    Employee Turnover Analytics

    Analyze HR datasets and build predictive models to identify factors contributing to employee attrition and improve workforce retention strategies.

  • Project 12

    Creating Designs by Leveraging OpenAI and Gradio UI

    Build an AI-powered application that generates marketing designs such as banners and posters using OpenAI image models and a Gradio interface.

  • Project 13

    Home Loan Data Analysis

    Build a deep learning model to predict loan default risk using historical financial data while handling multiple features and imbalanced datasets.

  • Project 14

    Sales Forecasting

    Build a time-series forecasting model to predict restaurant item demand using historical sales data to improve planning and operational decisions.

Disclaimer - The projects have been built leveraging real publicly available datasets from organizations.

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An Immersive Learning Experience

Peer to Peer engagement

Get the real classroom experience. Interact with learners and engage with mentors in real-time via Slack.

Flexi Learn

Missed a class? Access recordings to always maintain learning progress and keep up with your cohort.

Mentoring session(s)

Expert guidance sessions from mentors for doubt clarifications, project assistance, and learning support.

Learning Support

Get a dedicated Cohort Manager for all your queries and help you succeed at every learning step.

Peer to Peer engagement
Get the real classroom experience. Interact with learners and engage with mentors in real-time via Slack.
Flexi Learn
Mentoring session(s)
Learning Support

Program Trainers

  • Bassel Dakhlallah

    Bassel Dakhlallah

    13+ years of experience

    Data Analytics & Engineering Leader

  • Jerome Benton

    Jerome Benton

    13+ years of experience

    AI Engineer Lead

  • Ashutosh Malgaonkar

    Ashutosh Malgaonkar

    13+ years of experience

    Principal Data Scientist

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Career Support

Simplilearn Career Assistance

Simplilearn’s Career Services program, offered in partnership with Prentus, is a service that helps you to be career-ready for the workforce and land your dream job in U.S. markets.
Access to workshops, networking tools, and community support

Access to workshops, networking tools, and community support

Stay on top of your job hunt with a smart tracker and job board

Stay on top of your job hunt with a smart tracker and job board

Build an ATS-friendly resume using the AI Resume Builder

Build an ATS-friendly resume using the AI Resume Builder

Practice anytime with the AI-powered Mock Interview Coach

Practice anytime with the AI-powered Mock Interview Coach

Join the Industry: Career Outlook

Organizations are investing heavily in AI technologies to automate workflows, improve decision-making, and build intelligent products, creating strong demand for professionals with practical AI and machine learning expertise.

Job Icon30.6%

Projected CAGR of the global AI market from 2026 to 2033.

Source: Grand View Research
Job Icon28%

Higher avg. salary for roles with AI skills vs those without.

Source: Lightcast
Job Icon$158,750

Typical annual median salary for AI-related roles in the United States.

Source: Axial Search

Batch Profile

This program caters to working professionals from a variety of industries and backgrounds; the diversity of our students adds richness to class discussions and interactions.

  • Industry
    The class consists of learners from excellent organizations and diverse industries
    Industry
    Information Technology - 43%Manufacturing - 20%Software & Product - 13%Pharma & Healthcare - 7%BFSI - 7%Others - 10%
    Companies
    SAP
    Netflix
    Amazon
    Deloitte
    Wells Fargo
    Bosch
    JP Morgan Chase
    IBM
    Microsoft UMass

Admission Details

Application Process

The application process consists of three simple steps. An offer of admission will be made to the selected candidates and accepted by the candidates by paying the admission fee.

STEP 1

Submit Application

Tell us a bit about yourself and why you want to do this program

STEP 2

Reserve Your Seat

An admission panel will shortlist candidates based on their application

STEP 3

Start Learning

Selected candidates can begin the program within 1-2 weeks

Eligibility Criteria

For admission to this AI Program, candidates should:

Have 2+ years of work experience (preferred but not mandatory)
Be 18+ years old with a high school diploma or equivalent
Have a basic understanding of programming concepts and mathematics

Admission Fee & Financing

The admission fee for this program is $5,500

Financing Options

We are dedicated to making our programs accessible. We are committed to helping you find a way to budget for this program and offer a variety of financing options to make it more economical.

Total Program Fee

$5,500

Pay In Installments, as low as

$550/month

You can pay monthly installments for Post Graduate Programs using Splitit or Klarna payment option with low APR and no hidden fees.

Apply Now

Program Benefits

  • Earn a certificate in AI from UCSB PaCE and Simplilearn
  • Work on 14+ projects across different domains
  • Learn AI, ML, GenAI, and MLOps in a single program
  • Develop practical skills to build scable AI solutions
  • Exposure to 30+ tools, including Python, PyTorch, and Keras

Program Cohorts

There are no cohorts available in your region currently

Got Questions Regarding Cohort Dates?

FAQs

  • What is the nature of collaboration between Simplilearn and UCSB PaCE?

    UC Santa Barbara Professional and Continuing Education (UCSB PaCE) provides academic oversight for the program. This includes UCSB PaCE reviewed curriculum being delivered by instructors, who are vetted by UCSB PaCE. Upon successful completion, learners receive a co-branded certificate from UCSB PaCE & Simplilearn.

  • Can beginners enroll in this machine learning course, or is prior experience required?

    Yes, beginners can enroll in this program, as it starts with foundational concepts, including a Python refresher with AI and data science. However, it is recommended that learners have:

    • A basic understanding of programming
    • Foundational knowledge of mathematics and statistics
    • Minimum age 18, with a high school diploma or equivalent

    Disclaimer: Beginners may require additional time and effort to complete the program successfully. While the program may be rigorous, successful completion is achievable with consistent effort.

  • Is this AI ML course suitable for working professionals?

    Yes, the program is designed to fit around a busy work schedule. With online live classes and recorded sessions for catch-up, you can learn at your own pace. The recommended commitment is around 8-10 hours per week, making it manageable alongside a full-time job.

  • Is the curriculum aligned with current trends in AI ML courses and industry needs?

    Yes, the curriculum covers in-demand AI topics such as machine learning, deep learning, generative AI, large language models (LLMs), agentic AI, and MLOps, ensuring alignment with current industry trends.

  • What are the refund or withdrawal policies for this machine learning online course?

    To qualify for a refund, you must submit your refund request within 7 days from the start date of the regular class (Live or Recorded as the case maybe) whether attended or not. Any refund request failing to meet this requirement will not be accepted, and no refund will be provided.

    For instructor-led training & University Partnered programs, Simplilearn reserves the right to reschedule/cancel a class/session due to any unavoidable circumstances. Simplilearn will reschedule any canceled class/session.

    For University Partnered Programs: Click here for Refund Policy.

  • Acknowledgement
  • PMP, PMI, PMBOK, CAPM, PgMP, PfMP, ACP, PBA, RMP, SP, OPM3 and the PMI ATP seal are the registered marks of the Project Management Institute, Inc.
  • *All trademarks are the property of their respective owners and their inclusion does not imply endorsement or affiliation.
  • Career Impact Results vary based on experience and numerous factors.