Data Science Program (DSAIT02)

Course Outline: Digital Business Acumen

Module 1: Enterprise Digital Vision and Roadmap

• Identify the enterprise Digital Transformation vision and roadmap
• Understand the importance of Business Model Innovation in the context to enterprise’s Digital Transformation journey.
• Define business outcomes and strategic initiatives
• Determine your Digital Skills, Talent, Technology and Organizational requirements

Module 2: Research and Plan

• Assess the Digital Maturity of incumbent’s organization
• Assess Product and Services Digital readiness
• Assess the Digital technology readiness
• Assess the ecosystem and partnership readiness
• Assess the Digital cultural (‘AI ready culture’) readiness
• Planning the Digital journey based on Digital Maturity

Module 3: Prepare and Blueprint

• Best practice and mistakes to avoid
• Identify the workforce requirements, technologies and capabilities
• Address security, organizational and change management needs
• Build your “coalition of the willing

Module 4: Implement & Scale

• How to measure and validate success in DX projects
• Impact of Change Management
• Significance of Knowledge Management
• Learn to scale to the rest of the enterprise

Course Outline: 21st Century Business skills

• Design Thinking
• Critical Thinking
• Communication & Empathy
• Collaboration
• Creativity and Attitude
• Planning and Organizing
• Customer-centric Focus
• Working with Tools & Technology
• Dynamic self-initiated re-skilling
• Professional Networking
• Ethics
• Mindfulness
• Adaptive Mindset

Course Outline: Data Analytics

• Statistical methods for Data Analysis
• Machine Learning Essentials
• Data Mining
• Text Data Mining
• Predictive Analytics
• Data Visualization, Modeling & Optimization

Course Outline: Data Management

• General principles in Data Management & Organization
• Data Management Systems
• Data Management & Enterprise Data Infrastructure
• Data Governance, Privacy & Ethics
• Large Scale Data storage
• Digital libraries & Data archiving

Course Outline: Data Science Engineering

• Big Data infrastructure & technologies
• Infrastructure & Platforms for Data Science applications
• Cloud computing technologies for Big Data & Data Analytics
• Big Data Systems organization & engineering
• Data Science Applications design

Course Outline: Domain Analytics – Finance, Energy (Oil & Gas), Healthcare or Manufacturing

• Domain-specific Analytics Foundations
• Domain-specific organization & enterprise management

Course Outline: Advanced Data Analytics

• Graph theory
• Information theory
• Deep Learning
• Anomaly detection
• Time series analysis
• Risk Simulation & queueing
• Network Optimization

Course Outline: Advanced Data Management

• Advanced Big Data storage infrastructure and operations
• Storage architectures, distributed files systems (HDFS, Ceph, Lustre, Gluster, etc.)
• Data storage redundancy and backup
• Data factories, data pipelines
• Cloud based storage, Data Lakes
• Digital libraries and archives organization
• Information Retrieval
• Data curation and provenance
• Search Engines technologies

Course Outline: Advanced Data Science Engineering

• Infrastructure, applications and data security
• Data encryption and key management
• Access Control and Identity Management
• Security services management, including compliance and certification
• Data anonymization
• Data privacy
• Models and languages for complex interlinked data presentation and visualization
• Agile development methods, platforms and tools
• DevOps and continuous deployment and improvement paradigm
• Decision Analysis and Decision Support Systems
• Predictive analytics and predictive forecasting
• Data Analysis and statistics
• Data warehousing and Data Mining
• Multimedia information systems
• Enterprise information systems
• Collaborative and social computing systems and tools