Applied Data Science Program: Leveraging AI for Effective Decision-Making
- Offered byMIT Professional Education
Applied Data Science Program: Leveraging AI for Effective Decision-Making at MIT Professional Education Overview
Duration | 12 weeks |
Start from | Start Now |
Mode of learning | Online |
Difficulty level | Intermediate |
Official Website | Go to Website  |
Credential | Certificate |
- Overview
- Highlights
- Course Details
- Curriculum
- Admission Process
Applied Data Science Program: Leveraging AI for Effective Decision-Making at MIT Professional Education Highlights
- Earn a certificate after completion of course from MIT Professional Education
Applied Data Science Program: Leveraging AI for Effective Decision-Making at MIT Professional Education Course details
Professionals who are interested in a career in Data Science and Machine Learning
Professionals interested in leading Data Science and Machine Learning initiatives at their companies
Entrepreneurs interested in innovation using Data Science and Machine Learning
Understand the intricacies of data science techniques and their applications to real-world problems
Implement various machine learning techniques to solve complex problems and make data-driven business decisions
Explore the realms of Machine Learning, Deep Learning, and Neural Networks, and how they can be applied to areas such as Computer Vision
Develop strong foundations in Python, mathematics, and statistics for data science
Understand the theory behind recommendation systems and explore their applications to multiple industries and business contexts
Build an industry-ready portfolio of projects to demonstrate your ability to extract business insights from data
MIT Professional Education's Applied Data Science Program: Leveraging AI for Effective Decision-Making, with a curriculum developed and taught by MIT faculty, is delivered in collaboration with Great Learning
In this 12-week program, you will be able to upgrade your data analytics skills by learning the theory and practical application of supervised and unsupervised learning, time-series analysis, neural networks, recommendation engines, regression, and computer vision, to name a few
Applied Data Science Program: Leveraging AI for Effective Decision-Making at MIT Professional Education Curriculum
Week 1&2 - Module 1
Foundations for Data Science
Python Foundations - Libraries: Pandas, NumPy, Arrays and Matrix handling, Visualization, Exploratory Data Analysis (EDA)
Statistics Foundations: Basic/Descriptive Statistics, Distributions (Binomial, Poisson, etc.), Bayes, Inferential Statistics
Week 3 - Module 2
Data Analysis & Visualization
Exploratory Data Analysis, Visualization (PCA, MDS and t-SNE) for visualization and batch correction
Introduction to Unsupervised Learning: Clustering includes - Hierarchical,
K-Means, DBSCAN, Gaussian Mixture
Networks: Examples (data as a network versus network to represent dependence among variables), determine important nodes and edges in a network, clustering in a network
Week 4 - Module 3
Machine Learning
Introduction to Supervised Learning -Regression
Model Evaluation- Cross Validation and Bootstrapping
Introduction to Supervised Learning-Classification
Week 5 - Module 4
Practical Data Science
Decision Trees
Random Forest
Time Series (Introduction)
Week 6 - Learning Break
Week 7 - Module 5
Deep learning
Intro to Neural Networks
Convolutional Neural Networks
Graph Neural Networks
Week 8 - Module 6
Recommendation Systems
Intro to Recommendation Systems
Matrix
Tensor, NN for Recommendation Systems
Week 9 - Project Week
Time for participants to finish and submit their projects
Week 10-12 - Module 7
Capstone Project
Week 10: Milestone 1
Week 11: Milestone 2
Week 12: Synthesis + Presentation
Applied Data Science Program: Leveraging AI for Effective Decision-Making at MIT Professional Education Admission Process
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Applied Data Science Program: Leveraging AI for Effective Decision-Making