Emeritus Institute of Management
Professional Certificate in Machine Learning and Artificial Intelligence

Online, Singapore

DEGREE TYPE

Certificate

DURATION

6 months

LANGUAGES

English

PACE

Full time, Part time

APPLICATION DEADLINE

EARLIEST START DATE

STUDY FORMAT

Distance Learning

Key Summary

About: The Professional Certificate in Machine Learning and Artificial Intelligence at UC Berkeley, built with the College of Engineering and the Haas School of Business, teaches foundational and advanced ML and AI concepts, business applications, hands-on tools and practical projects. You'll study models, algorithms, deep learning and data science over six months, with instruction from world-class faculty and programme facilitation by Emeritus.

Career Outcomes: Emeritus provides career preparation services: elevator pitch, LinkedIn, resume, interview and salary negotiation, and programme facilitators and career coaches. Graduates can also target roles like ML engineer, data scientist, AI engineer; job placement is not guaranteed.

Launch Your Career in ML/AI

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.

$120,844 The average salary for an AI/ML engineer in the US in 2022 (Source: Glassdoor)
97 million The estimated number of new AI-related jobs between 2022 and 2025 (Source: Forbes)
$15.7 trillion AI's projected contribution to the global economy by 2030 (Source: Forbes)

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.