Get a 2 year Masters in Data Science with the Latest Cutting Edge Curriculum from One of the Top 100 Best Global Universities in the World, University of Arizona. Ranked in the Top 100 (Best Global Universities in the world) by U.S. News and World report.
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.
Complete all the courses successfully to obtain this recognition from the University of Arizona.
- Earn a Master of Science in Data Science degrees
- Get University of Arizona alumni status
- Get ID cards (chargeable) and email IDs from University of Arizona.
- A minimum of 70% score (C grade) is required to pass each course. A minimum of 3.0 CGPA is required to pass the entire program.
STUDY MODEL
Online format, Coaching (1:1)
ACCREDITATION
Accredited by Institute of Analytics UK (IOA)
DURATION
24 months with 12-15 hours per week
ELIGIBILITY
Bachelor Degree or equivalent, online test, English language proficiency
FEES
USD 11,000
VALUE-ADD
Industry Readiness Assessments
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
