The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
CourtlynPromotion and Events Specialist
Gain cutting-edge ML/AI skills and accelerate your career in this 6-month online program.Download Brochure
August 30, 2023
6 months, online
15–20 hours per week
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.
CourtlynPromotion and Events Specialist
Based 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, 2023 .
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Interested in exploring other UC Berkeley Executive Education programs? Learn more >
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 AI/ML engineer in the US in 2022
The estimated number of new AI-related jobs between 2022 and 2025
AI's projected contribution to the global economy by 2030
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:
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
Over the course of this program, you will gain hands-on coding experience with Python, Jupyter, pandas, Seaborn, Plotly, and GitHub.
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... More info
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... More info
Researcher and lecturer with the Mechanical Engineering Department and the Institute of Transportation Studies at UC BerkeleyGabriel 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.
Associate Teaching Professor with the department of Electrical Engineering and Computer Sciences at UC BerkeleyJoshua 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.
Associate Professor of Business and Public Policy and Economics at UC Berkeley
Reed Walker is an associate professor of business and public policy and economics at UC Berkeley. His research explores the social costs of environmental externalities, such as air pollution, and how regulations to limit these externalities contribute to gains and/or losses to the economy. He is the faculty codirector of the UC Berkeley Opportunity Lab’s Climate and Environment Initiative. He is also a research associate at the Energy Institute at Berkeley, a faculty research fellow at the National Bureau of Economic Research, and a research fellow at IZA. He received his Ph.D. in economics from Columbia University.
Associate Professor | Egon & Joan Von Kaschnitz Distinguished Professorship
Jonathan Kolstad is an Associate Professor of Economic Analysis and Policy at Berkeley Haas and a research associate at the National Bureau of Economic Research. He is also the codirector of the Health Initiative at the UC Berkeley Opportunity Lab. He is an economist whose research interests lie at the intersection of health economics, industrial organization, and public economics. He is particularly interested in finding new models and unique data that can account for the complexity of markets in health care, notably the role of information asymmetries and incentives. He is also a cofounder and was chief data scientist at Picwell. He received his Ph.D. from Harvard University and B.A. from Stanford University.
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:
Enrolling in the Professional Certificate in Machine Learning and Artificial Intelligence program can become your first step toward pursuing the UC Berkeley Executive Education Certificate of Business Excellence (COBE). The Certificate of Business Excellence gives individuals the opportunity to acquire and hone new skills and do it on a timeline that works with your busy schedule. Participants will earn a mark of distinction with certification from a world-class university, and enjoy the flexibility of completing the program in up to three years.
Learn more about the program and associated alumni benefits here.
Networking and events
Exclusive Berkeley Resources
News and communication
Note: All benefits subject to change.
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% of the required activities including a capstone project (if any) to obtain the certificate of completion. This program also counts toward a Certificate of Business Excellence.
Successful completion of this program fulfills four curriculum days (minimum requirement of 17 curriculum days) towards the UC Berkeley Certificate of Business Excellence (COBE).
Learn more on how it works here.
Note: 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.
After reviewing the information on the program landing page, we recommend you submit the short form above to gain access to the program brochure, which includes more in-depth information. If you still have questions on whether this program is a good fit for you, please email firstname.lastname@example.org, and a dedicated program advisor will follow up with you very shortly.
Some programs do have prerequisites, particularly the more technical ones. This information will be noted on the program landing page and in the program brochure. If you are uncertain about program prerequisites and your capabilities, please email us at email@example.com for assistance.
This is a graded program. You must complete a combination of individual assignments, quizzes, and a final project. Each component carries a certain number of points, and a cumulative score of 75 percent is required to pass and obtain your professional certificate.
The primary objective of this program is to give you the skills you need to be prepared for a job in this field. While eligible participants will receive career coaching and support and may receive introductions to our hiring partners, job placement is not guaranteed.
Each program includes an estimated learner effort per week. This is referenced at the top of the program landing page under the “Duration” section and in the program brochure, which you can obtain by submitting the short form at the top of this web page.
You will divide your learning time between viewing recorded coding demos, and video lectures, contributing to class discussions, completing assignments, projects, and knowledge checks, and attending optional weekly live sessions with industry experts and program leaders.
The program is accessed through the custom learning portal. This portal will give you access to all program-related content such as video lectures, assignments, and discussions. Live office hours will be conducted using a webinar tool.
The video lectures and assignments are accessible weekly throughout the program. In the event you miss a live session, a recording will be made available.
Faculty video lectures are recorded, allowing you to watch these on your own schedule. However, participation in optional live weekly live sessions and discussion boards is highly encouraged. Live sessions will give you the opportunity to draw on the coding experience of our industry-experienced program leaders to answer your questions and help reach your learning goals. The discussion boards are also an integral part of the learning experience, giving you and your peers the opportunity to learn together and receive guidance from the moderators.
You can download video transcripts, assignment templates, readings, etc. However, the video lectures are only available for streaming and require an internet connection.
You can communicate with other participants through our learning platform. You will be able to form groups based on your interests and location. A direct messaging feature is also available through the platform.
More than 300,000 learners across 200 countries have chosen to advance their skills with Emeritus and its educational learning partners. In fact, 90 percent of the respondents of a recent survey across all our programs said that their learning outcomes were met or exceeded.
All the contents of the course would be made available to students at the commencement of the course. However, to ensure the program delivers the desired learning outcomes the students may appoint Emeritus to manage the delivery of the program in a cohort-based manner the cost of which is already included in the overall course fee of the course.
A dedicated program support team is available 24/5 (Monday to Friday) to answer questions about the learning platform, technical issues, or anything else that may affect your learning experience.
Each program includes an estimated learner effort per week, so you can gauge what is required before you enroll. This is referenced at the top of the program landing page under the “Duration” section and in the program brochure, which you can obtain by submitting the short form at the top of this web page. All programs are designed to fit into your working life.
This program is scored as a pass or no-pass; participants must complete the required activities to pass and obtain the certificate of completion. Some programs include a final project submission or other assignments to obtain passing status. This information will be noted in the program brochure. Please contact us at firstname.lastname@example.org if you need further clarification of any specific program requirements.
Upon successful completion of the program, you will receive a smart digital certificate. The smart digital certificate can be shared with friends, family, schools, or potential employers. You can use it on your cover letter, résumé, and/or display it on your LinkedIn profile.
The digital certificate will be sent approximately two weeks after the program, once grading is complete.
No, only verified digital certificates will be issued upon successful completion. This allows you to share your credentials on social platforms such as LinkedIn, Facebook, and Twitter.
No, there is no alumni status granted for this program. In some cases, there are credits that count toward a higher level of certification. This information will be clearly noted in the program brochure.
You will have access to the learning platform and all program materials (videos excluded) for one full year following the program end date. Access to the learning platform is restricted to registered participants per the terms of agreement.
To successfully complete this course/program(me) online, you must have access to a device meeting the minimum requirements, found here. In addition, Microsoft Office or similar product and a PDF viewer are required to access documents, spreadsheets, presentations, PDF files, and transcripts in all programs. There will be additional software and tools required, such as Anaconda, GitHub and Zoom. Please check the learning platform on the first day of class.
Yes, the learning platform is accessed via the internet and video content is not available for download. You can download files of video transcripts, assignment templates, readings, etc. Video lectures must be streamed via the internet and webinars and small group sessions will require an internet connection.
Yes, you can do the bank remittance in USD via wire transfer. Please contact your program advisor for more details.
Yes flexible payment options are available for this program. We partner with loan providers to offer you flexible and transparent loan options. More information about loan financing is available here. Installment payments are also available—; you can find the options here.
Yes, the program fee is inclusive of any taxes with the exception of GST for Singapore residents.
After a participant has withdrawn, they will no longer be able to attend live sessions or 1:1 sessions with course leaders, mentors, or career coaches; submit work for review; or access their program dashboard or curriculum.
Participants who would like to cancel their enrollment should email ProgramSupport@Emeritus.org or visit the “Support” tab in the learning platform to obtain a copy of the Withdrawal Request Form. This form must be submitted by midnight UTC of the last day of the trial period to be eligible for a full refund. No cancellations will be processed unless this form is received. Refunds will be issued within 30 days after the effective date of withdrawal or dismissal.
Participants have the option to request a deferral to a future cohort within the first 30 days from their program start date. Cohort changes may be made only once per enrollment and are subject to the availability of cohorts and scheduled at the discretion of Emeritus. Participants requesting a deferral must be in good academic standing. Participants who would like to defer their enrollment should email ProgramSupport@Emeritus.org or visit the “Support” tab in the learning platform to obtain a copy of the Deferral Request Form.