Become a data-driven leader with a one-of-its-kind Executive Program in Data Science and Machine Learning. Taught by top Academicians & industry experts, this 360 degree program will put you at the forefront of the Data Science & Machine Learning revolution. No prior coding experience required.
This program is offered in partnership with upGrad, a global leader in higher online education with 2 million learners across 100 countries worldwide. With the latest technology, pedagogy, industry partners and world-class faculty, upGrad creates immersive online learning experiences for learners globally.
On successful completion of the Program, you receive this certificate from University of Maryland’s Robert H. Smith School of Business.
- Earn 3 certificates which cover the breadth of data science and machine learning skills in just 12 months
- Showcase your certificate from a Top 20 U.S. Public university
- Gain demonstrable hands-on skills in data science and machine learning
STUDY MODEL
Online, weekly live sessions, small group coaching
ACCREDITATION
University of Maryland accredited
DURATION
12 months
ELIGIBILITY
Diploma or Bachelor Degree, some experience of programming languages preferred but not essential, English language proficiency
FEES
USD 3,200
VALUE-ADD
Personalized industry mentorship
Data Analysis in Excel
Introduction to DS Landscape
Python Programming Essentials I – Variables, Expressions, and Control Statements
Python Programming Essentials II – Functions and Data Structures
Python Libraries for Data Science – NumPy
Python Libraries for Data Science – Pandas
Python Assignment
Data Analysis using SQL
Practical Data Considerations: Data Cleaning and Preparation
Course Project: Python
Exploratory Data Analysis
Visualization in Python
Visualization using Tableau
Data Storytelling
Visualisation and Storytelling Assignment
Inferential Statistics
Hypothesis Testing
Designing Business Experiments
Course Project: Statistics
Linear Regression in a predictive setting
Introduction to Classification: Logistic Regression
Evaluation methods in Classification Models
Model Selection & Practical Consideration around Modelling + KNN
Decision Tree Models
Introduction to Ensemble Models: Random Forest & Boosting
Assignment
Unsupervised Learning: Clustering
Unsupervised Learning: Association Rules Mining (Market Basket Analysis)
Course Project: Machine Learning
Capstone Project
Introduction to Deep Learning
Classification & Regression Models using Neural Networks
Introduction to Convolutional Neural Networks
Introduction to Natural Language Processing
Modelling on Text data
Assignment
Framework to AI & Business Strategy
Executing AI Strategy
Advanced Python Programming
Advanced SQL
Introduction to Time Series
Recommender Systems
DL in Tf & Optimization (Optional)
RNN
Applications in CV
Assignment
Capstone Project II
