Master Courses
.Health and Sciences.
Master of Data Science and Analytics
Overview
This master program provides an in-depth understanding of data science methodologies and their applications in real-world scenarios. Students will work on data-driven projects, exploring tools and techniques for data mining, predictive modeling, and big data analytics.
Duration: 1 to 2 years (Full-time or Part-time options available).
Learning Method: Online, face-to-face, or hybrid.
Objective: To develop data science professionals who can derive actionable insights and drive innovation across industries.
Minimum qualification: Completion of a Bachelor’s degree in data science, computer science, statistics, mathematics, or related fields.
Recommended Background: Proficiency in programming languages (e.g., Python, R). Basic understanding of statistical methods and algorithms.
1. Industry-Aligned Curriculum: Developed in collaboration with data science experts.
2. Hands-On Projects: Real-world data challenges across multiple industries.
3. Advanced Tools: Training in Python, R, SQL, Tableau, Hadoop, and TensorFlow.
4. Capstone Project: Application of learned techniques to a large-scale data project.
1. Technical Proficiency: Master key tools and frameworks used in data science.
2. Data Analysis Expertise: Derive actionable insights from structured and unstructured data.
3. Machine Learning Mastery: Develop predictive models to solve complex problems.
4. Business Acumen: Bridge the gap between technical analysis and business strategy.
Module Guide
1. Introduction to Data Science: Fundamentals of data analysis and applications.
2. Statistical Methods for Data Science: Inferential statistics and hypothesis testing.
3. Data Engineering and Big Data: Techniques for handling and processing large datasets.
4. Programming for Data Science: Mastering Python and R for data analysis.
1. Machine Learning and AI: Supervised, unsupervised, and deep learning models.
2. Data Visualization and Storytelling: Tools and techniques for effective communication.
3. Predictive Analytics: Forecasting and trend analysis using advanced algorithms.
4. Capstone Project: End-to-end data science project demonstrating analytical and technical skills.
Certification
Graduates earn a Master of Data Science and Analytics degree from Quantum Infinity Education, recognized internationally and certifying expertise in data science and analytics.
Course Fees
Fees for domestic students range from $25,000 to $30,000 per year. The cost reflects the comprehensive learning resources, industry exposure, and high-quality education provided. Flexible payment plans and installment options are available.
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