Program Overview
In today's data-driven world, the demand for skilled professionals who can harness the power of data is ever-growing. Digicrome presents a comprehensive Master's in Data Science and Analytics program designed to equip individuals with advanced analytical skills to derive insights from big data and develop automated artificial intelligence processes. This practical online program integrates project-based learning, case studies, simulations, and specific electives tailored to meet the analytical needs of various industry sectors. With tie-ups with corporate partners, students gain access to real-world data sets and networking opportunities, enhancing their career prospects.
Audience Profile:
This program is ideal for:
- IT Professionals
- Analytics Managers
- Business Analysts
- Banking and Finance Professionals
- Marketing Managers
- Supply Chain Network Managers
- Beginners or Recent Graduates in Bachelors or Master’s Degree
Eligibility Criteria:
- Minimum graduation in any discipline
- 0-5 years of work experience (freshers may also apply)
- No coding experience required
Program Objectives:
The Master's in Data Science and Analytics program aims to:
- Develop proficiency in data management, mining, and visualization
- Provide hands-on experience with statistical analysis and predictive modelling
- Equip students with machine learning and deep learning techniques
- Foster effective storytelling and business value generation through data insights
Learning Outcome:
Upon completion, graduates will:
- Enhance decision-making processes
- Align strategies with business objectives
- Improve cost-efficiency and competitiveness
- Gain a unified view of enterprise information
- Increase revenue through data-driven insights
Why Digicrome?
- Over 125,000 students trained
- 4 million hours of learning delivered
- Top 10 ranked programs
- Expert faculty comprising 500+ industry specialists
- Rigorous curriculum designed by academics and industry experts
Admission Process:
- Apply online through the Digicrome website
- Applications reviewed by faculty panels
- Selected candidates undergo an interview assessment
- The admission proposal was extended to successful candidates
Career Opportunities:
Upon completion of the program, graduates can pursue various roles, including:
- Data Scientist
- Quantitative Analyst
- Business Analyst
- Data Analyst
- Business Analytics Manager/Consultant
Unlock the potential of data and propel your career forward with Digicrome’s Master's in Data Science and Analytics program. Apply now and embark on a journey towards becoming a proficient data scientist.
Masters in Data Science and Analytics
- ₹70000.00
Features
- Job Assistance
- Industry Based Trainers
- Multiple Simulation Exams
- Course Completion Certificate
Key Highlights
- Job Assistance
- Industry Based Trainers
- Multiple Simulation Exams
- Course Completion Certificate
- Expert Experienced Trainers
- 1:1 Doubt Session
- Learning Management System
- 24*7 Career Support
Program Objective
- Introduction to Business Analytics
- R for Data Science
- Introduction to R and R-Studio
- Dealing with Data using R
- Visualization using R
- Descriptive Statistics
- Introduction to Probability
- Probability Distributions
- Hypothesis Testing and Estimation
- Goodness of Fit
- Fundamentals of Finance
- Working Capital Management
- Capital Budgeting
- Capital Structure
- Core Concepts of Marketing
- Customer Life Time Value
- Analysis of Variance
- Regression Analysis
- Dimension Reduction Techniques
- Introduction to Supervised and Unsupervised Learning
- Clustering
- Decision Trees
- Random Forest
- Neural Networks
- Multiple Linear Regression
- Logistic Regression
- Linear Discriminant Analysis
- Introduction to Time Series
- Correlation
- Forecasting
- Autoregressive models
- Handling Unstructured Data
- Machine Learning Algorithms
- Bias Variance trade-off
- Handling Unbalanced Data
- Boosting
- Model Validation
- Linear programming
- Goal Programming
- Integer Programming
- Mixed Integer Programming
- Distribution and Network Models
- Marketing and Retail Terminologies
- Customer Analytics
- KNIME
- Retail Dashboard
- Customer Churn
- Association Rules Mining
- Web Analytics: Understanding the metrics
- Basic & Advanced Web Metrics
- Google Analytics: Demo & Hands on
- Campaign Analytics
- Text Mining
- Why Credit Risk-Using a market case study
- Comparison of Credit Risk Models
- Overview of Probability of Default (PD) Modeling
- PD Models, types of models, Steps to make a good model
- Market Risk
- Value at Risk - using stock case study
- Introduction to Supply Chain
- Dealing with Demand uncertainty
- Designing Optimal Strategy using Case Study
- Inventory Control & Management
- Inventory classification
- Inventory Modeling
- Costs Involved in Inventory
- Economic Order Quantity
- Forecasting
- Advanced Forecasting Methods
- Examples & Case Studies
- Introduction to Data Visualization
- Introduction to Tableau
- Basic charts and dashboard
- Descriptive Statistics, Dimensions and Measures
- Visual analytics: Storytelling through data
- Dashboard design & principles
- Advanced design components/ principles : Enhancing the power of dashboards
- Special chart types
- Case Study: Hands on using Tableau
- Integrate Tableau with Google Sheets
- R and Python
- Tableau
- SAS (Online Module)
- Hackathons
- Group Presentation