The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events Specialist
Gain cutting-edge ML/AI skills and accelerate your career in this 6-month online program.
August 30, 2022
6 months, online
15–20 hours per week
US$7,500 or get US$500 off with a referral
Our participants tell us that taking this program together with their colleagues helps to share common language and accelerate impact.
We hope you find the same. Special pricing is available for groups.
The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events SpecialistBased on the information you provided, your team is eligible for a special discount, for Professional Certificate in Machine Learning & Artificial Intelligence starting on August 30, 2022 .
We’ve sent you an email with enrollment next steps. If you’re ready to enroll now, click the button below.
Have questions? Email us at group-enrollments@emeritus.org.Machine learning (ML) and artificial intelligence (AI) are transforming the way organizations do business and how consumers live. That's why IT professionals with the specialized knowledge and skills to develop the next generation of ML/AI technology innovations are in immediate demand globally and across industries.
So how can you kick-start your career in this exciting, in-demand field? The Professional Certificate in Machine Learning and Artificial Intelligence from UC Berkeley (ranked the #1 university in the world by Forbes magazine) is built in collaboration with the College of Engineering and the Haas School of Business.
In six months, you will gain foundational as well as advanced knowledge of ML/AI along with insights into the business applications of these technologies from UC Berkeley's world-class faculty. You will gain practical, hands-on experience using cutting-edge ML/AI tools in addition to career guidance to succeed in this fast-paced field. Take the next step in your career by gaining market-ready ML/AI skills with this professional certificate program.
The average salary for an entry-level ML engineer with zero to two years of experience
Job postings in the US asking for ML or AI as a skill from July 2020 to June 2021
Annual compound growth rate of the global AI market
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:
Applicants must have:
Also recommended:
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
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
Over the course of this program, you will gain hands-on coding experience with Python, Jupyter, pandas, Seaborn, Plotly, and GitHub.
Gabriel Gomes
Joshua Hug
Gabriel Gomes
Researcher and lecturer with the Mechanical Engineering Department and the Institute of Transportation Studies at UC Berkeley
Gabriel Gomes is a researcher and lecturer with the Mechanical Engineering Department and the Institute of Transportation Studies at UC Berkeley. He received a doctorate degree in automatic control theory in 2004 from UC Berkeley. Since then, he has focused his research on various problems in the modeling, simulation, and control of traffic networks. As a lecturer at UC Berkeley, he has taught courses in partial differential equations, control theory, and mathematical modeling. He also supervises capstone projects with the Master of Engineering program of the Fung Institute. These projects cover a wide range of topics, including robotics, solar energy, machine learning, natural language processing, traffic simulation, reinforcement learning, autonomous vehicles, and smart exercise machines. He is the author of over 50 papers in various areas of engineering.
Joshua Hug
Associate Teaching Professor with the department of Electrical Engineering and Computer Sciences at UC Berkeley
Joshua Hug has been with the department of Electrical Engineering and Computer Sciences at UC Berkeley since 2014 and was a lecturer at Princeton University from 2011 to 2014. He received his Ph.D. in 2011 from UC Berkeley, with research focused on computational models of bacterial signal processing and decision making. He received his B.S. in electrical engineering in 2003 from the University of Texas at Austin. In 2017, he received the Diane S. McEntyre Award for Excellence in Teaching Computer Science, and in 2018, he received the Jim and Donna Gray Award for Excellence in Undergraduate Teaching of Computer Science. He has taught courses in artificial intelligence, data structures, rule-based and generative art, information security, data science, and the social implications of computing.
Reed Walker
Jonathan Kolstad
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:
Career exercises focused on launching a career in ML/AI:
Get recognized! Upon successful completion of the program, UC Berkeley Executive Education grants a verified digital certificate of completion to participants. Participants must complete 80 percent of the required activities, including a capstone project, to obtain the certificate of completion. This program also counts toward a Certificate of Business Excellence.
Download BrochureNote: This program results in a digital certificate of completion and is not eligible for degree credit/CEUs. After successful completion of the program, your verified digital certificate will be emailed to you in the name you used when registering for the program. All certificate images are for illustrative purposes only and may be subject to change at the discretion of UC Berkeley College of Engineering, Haas School of Business, and Berkeley Executive Education.
Registration for this program is done through Emeritus. You can contact us at berkeley@emeritus.org or schedule a call with an advisor.
Flexible payment options available.