Data Science Program (DSAIT02) – Outline

Detailed Course Outline

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