Who should attend
The diploma requires an undergraduate knowledge of statistics (descriptive statistics, regression, sampling distributions, hypothesis testing, interval estimation etc.), calculus (derivatives), linear algebra (vectors & matrix transformation) and probability (conditional probability/Bayes theorem).
The admission process will involve a short screening test on the above topics to assess participant readiness for the diploma.
Participants are required to possess an intermediate knowledge of Python since all assignments/application projects will be done using the Python programming language. Emeritus offers a complimentary Python for Data Science certificate course to meet this prerequisite. Participants who successfully complete this certificate course will receive a certificate of completion from Emeritus Institute of Management.
- Minimum three years of professional work experience
- Employment history (CV/resume)
- University transcripts
- All candidates who have received their bachelor’s or other degree or diploma from an education institution where English is NOT the primary language of instruction are required to demonstrate English language proficiency through ANY ONE of the following methods
- Obtain a TOEFL minimum score of 550 for the paper based test or its equivalent
- Obtain an IELTS minimum score of 6.0 Obtain a Pearson Versant Test minimum score of 59
- Obtain a Certificate of Completion for a Certificate course offered by the Emeritus Institute of Management
- Submit a document which shows that the candidate has, for the last 24 months or more, worked in ANY ONE of these countries: Antigua and Barbuda, Australia, The Bahamas, Barbados, Belize, Canada, Dominica, Grenada, Guyana, India, Ireland, Jamaica, New Zealand, Singapore, South Africa, St Kitts and Nevis, St Lucia, St Vincent and the Grenadines, Trinidad and Tobago, United Kingdom, United States of America
- A completed Application Form
- Proof of diploma/degree in any field of study (your highest qualification should be submitted)
About the course
Artificial intelligence (AI) and machine learning algorithms are transforming systems, experiences, processes, and entire industries. It’s no wonder that business leaders see these data-driven technologies as fundamental for the future—and that practitioners fluent in both fields are in high demand.
We are fascinated by their world-changing potential, and we’ve created the Postgraduate Diploma in Machine Learning and Artificial Intelligence to help students understand the fundamentals of AI and machine learning and how to apply them to solve complex, real-world problems.
Emeritus and Columbia Engineering Executive Education
Columbia Engineering Executive Education is collaborating with online education provider Emeritus Institute of Management (Emeritus) to offer executive education courses.
An Emeritus Postgraduate Diploma contains multiple Emeritus Certificate courses created in collaboration with Columbia Engineering Executive Education, and may also include courses created independently by Emeritus. Upon successful completion, learners will be awarded a Postgraduate Diploma by Emeritus.
Module 1: Applied Machine Learning
- Maximum Likelihood, Least Squares, Regularization
- Bayesian Methods
- Bayes Rule, MAP Inference, Active Learning
- Foundational Classification Algorithms
- Nearest Neighbors, Perceptron, Logistic Regression
- Refinements to Classification
- Kernel Methods, Gaussian Process
- Intermediate Classification Algorithms
- SVM, Trees, Forests and Boosting
- Clustering Methods
- K-Means Clustering, E-M, Gaussian Mixtures
- Recommendation Systems
- Collaborative Filtering, Topic Modeling, PCA
- Sequential Data Models
- Markov and Hidden Markov Models, Kalman Filters
- Association Analysis
- Clustering Methods – II
- Model Comparisons, Analysis Considerations
Module 2: Applied Artificial Intelligence
- Introduction to Artificial Intelligence
- Intelligent Agents and Uninformed Search
- Heuristic Search
- Adversarial Search and Games
- Constraint Satisfaction Problems
- Reinforcement Learning
- Logical Agents
- AI applications: Natural Language Processing
- AI Applications and Course Review
Module 3: Capstone Project
You will create market segments using the US Census dataset and by applying the k-means clustering method.
Apply the Data Science workflow to a classic e-commerce dataset to predict retention and customer sales over time (Amazon sales dataset)
Natural Language Processing
Explore text analysis, text mining, sentiment analysis with classic text data sets (i.e. Twitter, Yelp, Wikipedia) and packages such as SpaCy and NLTK
Apply OpenAI Gym, TensorFlow, and PyTorch to train systems such as Stanford Question Answering Dataset
Constraint Satisfaction Problems
Implement constraint optimization techniques in TensorFlow for Loan Approvals dataset
Adversarial Search and Games
Apply decision making across voting election data (online voting data for US elections)
Apply advanced search techniques from Grid Search and Random Search to A* to identify parameters appropriate
Credit Card Fraud Detection
You will detect potential frauds using credit card transaction data. You will apply the random forest method to identify fraudulent transactions.
Human Activity Recognition
You will predict the human activity (walking, sitting, standing) that corresponds to the accelerometer and gyroscope measurements by applying the nearest neighbours technique
Movie Recommendation Engine
You will build a movie recommendation engine by applying collaborative filtering and topic modelling techniques. You use a dataset which contains 20 million viewer ratings of 27,000 movies.
House Price Prediction
You will write code to predict house prices based on several parameters available in the Ames City dataset compiled by Dean De Cock using least squares linear regression and Bayesian linear regression.
BENEFITS TO THE LEARNER
Enhance Your Career Capital
- Professional acceleration through our enriched leadership toolkit.
- Learn while you earn.
- Get noticed. Get ahead.
- Understand how to manage your career & personal brand.
Enhance Your Social Capital
- Make new, life-long connections with experienced business people from a wide variety of cultures, industries, and backgrounds.
- Inclusion in the Emeritus Network
- Invitation to Emeritus alumni events globally including career panels, CXO speaker series, and industry interactions.
Manage Your Brand Capital
- A Global Business Education on your resume
- Top 10 percent of the class achieves the status of Emeritus Scholars determined by the overall diploma GPA
Deepen Your Intellectual Capital
- World class curriculum and teaching by faculty from Columbia Engineering Executive Education.
- Peer-to-peer learning through learning circles, classroom discussions, and project reviews.
- Selective entrance criterion ensures you learn with the best.
Salleb-Aouissi’s specific and recent research interest is interdisciplinary and consists in leveraging advanced machine learning methods and large amounts of data to study medical problems, such as premature birth and infantile colic. Salleb-Aouissi cares about education and works toward advanci...
I am an associate professor in the Department of Electrical Engineering at Columbia University. I am also a member of the Data Science Institute at Columbia. Here is my CV. (Some other info about me here.) I received my Ph.D. in Electrical and Computer Engineering from Duke University, where I ...
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