Professional Certificate in Machine Learning and Artificial Intelligence

Who Is This Program For?

This program is designed to provide learners with the essential knowledge and practical applications of ML/AI tools and frameworks needed to transition into an exciting, high-demand career in this field. This program is for anyone with a technology or math background, including:

• IT and engineering professionals who want to unlock new opportunities for career growth or chart a cutting-edge career path
• Data and business analysts who want to gain better growth trajectories
• Recent science, technology, engineering, and mathematics (STEM) graduates and academics who want to enter the private sector and scale the positive impact of evolving technologies

Applicants must have:

• A bachelor's degree or higher
• Strong math skills
• Some programming experience

Also recommended:

• An educational background in STEM fields
• Technical work experience
• Some experience with Python, R, or SQL
• Some experience with statistics and calculus

Key Takeaways

• Develop a comprehensive understanding of ML/AI concepts and identify the best ML models to fit various business situations.
• Learn how to implement the ML/data science life cycle and devise cutting-edge solutions to real-life problems within your own organization.
• Interact and collaborate with industry experts to understand the technical and business applications of ML/AI.
• Develop a market-ready GitHub portfolio to show prospective employers.
• Learn from UC Berkeley's globally recognized faculty and gain a verified digital certificate of completion from UC Berkeley Executive Education.

Program Experience

• Learn from UC Berkeley's globally recognized faculty
• Earn a certificate of completion from UC Berkeley Executive Education
• Learn how to implement the ML/data science lifecycle within your own organization
• Build a GitHub portfolio to share with recruiters and potential employers

Tools and Resources in the Program

Over the course of this program, you will gain hands-on coding experience with Python, Jupyter, pandas, Seaborn, Plotly, and GitHub.

Program Topics

This program is organized into three main sections:

Section 1: Foundations of ML/AI

Your learning journey will commence with exploring the basic concepts, and industry-standard notations in ML/AI and exploring the real-world contexts for the data science lifecycle. It then progresses to drawing business conclusions from data sets and visualizations.

• Module 1: Introduction to Machine Learning
• Module 2: Fundamentals of Machine Learning
• Module 3: Introduction to Data Analysis
• Module 4: Fundamentals of Data Analysis
• Module 5: Practical Applications I

Section 2: ML/AI Techniques

In this section, you will gain hands-on experience with coding in Python to create k-means algorithms and apply functions. You will also learn how to predict outcomes using multiple linear regression models, create visual decision trees, and interpret various kinds of ML/AI decision models.

• Module 6: Clustering and Principal Component Analysis
• Module 7: Linear and Multiple Regression
• Module 8: Feature Engineering and Overfitting
• Module 9: Model Selection and Regularization
• Module 10: Time Series Analysis and Forecasting
• Module 11: Practical Applications II
• Module 12: Classification and k-Nearest Neighbors
• Module 13: Logistic Regression
• Module 14: Decision Trees
• Module 15: Gradient Descent and Optimization
• Module 16: Support Vector Machines
• Module 17: Practical Applications III

Section 3: Advanced Topics and Capstone

In the final section, you will gain a deeper understanding of advanced ML/AI concepts, such as Natural Language Processing and Deep Neural Networks. You will also conduct research and analysis to complete your capstone project in ML/AI.

• Module 18: Natural Language Processing
• Module 19: Recommendation Systems
• Module 20: Capstone I
• Module 21: Ensemble Techniques (GBM, XGB, and Random Forest)
• Module 22: Deep Neural Networks I
• Module 23: Deep Neural Networks II
• Module 24: Capstone II

Capstone Project

The knowledge gained each week in this ML/AI program prepares you to conduct your own research and analysis in a capstone project. You will gain the opportunity to interact with industry experts to identify a specific problem within your field and leverage their expertise along with the concepts, models, and tools taught in the program to devise a solution to your chosen problem. By the end of the program, you will come away with a professional-quality GitHub portfolio presentation that you can share on your LinkedIn profile or with potential employers.

Transitioning to a career in ML/AI engineering requires a variety of hard and soft skills. This program guides you as you navigate your journey to your new career path, including crafting an elevator pitch and communication tips. These services are provided by Emeritus, our learning collaborator for this program. The program support team includes program facilitators who will help you reach your learning goals and career coaches to guide you through your job search. Our primary goal is to give you the skills needed to be prepared for a job in this field; however, job placement is not guaranteed.

Emeritus provides the following career preparation services:

• Crafting your elevator pitch
• Navigating your job search
• LinkedIn profile guidance
• Interview tips and preparation
• Resume/cover letters
• Negotiating salary

Career exercises focused on launching a career in ML/AI:

• Job search and interviewing for ML/AI positions
• Communicating ML/AI concepts through presentation skills