Structured 3-Year progressive pathway from Diploma to full Bachelor's Degree.
Offered by EXPERTEXON in partnership with UGC recommended US University pathways.
Master Machine Learning, Big Data, Cloud Infrastructure, and Business Intelligence.
Offered by EXPERTEXON in affiliation with a **UGC Recommended US University**, this program equips students with cutting-edge analytical tools, enterprise system knowledge, and practical artificial intelligence capabilities demanded by modern multinational corporations.
The curriculum spans **100 Academic Credits** over 3 Years, allowing students to systematically build technical competence from Python programming and database management up to deep learning, predictive analytics, and executive decision support systems.
Graduates are prepared for high-demand roles such as **AI Business Analysts**, **Enterprise Systems Architects**, **Business Intelligence Consultants**, and **Digital Transformation Leaders**.
Year 1: Diploma (30 Credits)
Year 2: Higher Diploma (30 Credits)
Year 3: Degree Level (40 Credits)
Capstone: 10-Credit AI Research Project
Management theories, organizational structure, and operational environments.
Core hardware, software architectures, internet technologies, and system components.
Professional messaging, report generation, and formal presentation skills.
Basics of Python syntax, data types, control flow, functions, and logic building.
Linear algebra, calculus basics, descriptive statistics, and probability.
Consumer behavior, digital channels, and market research techniques.
Relational databases, SQL query design, normalization, and schema architecture.
Financial statements, double-entry bookkeeping, and cost estimation fundamentals.
Arrays, lists, trees, search/sort algorithms, and computational efficiency.
Overview of AI fields, machine learning concepts, logic, and intelligent agents.
Supervised/unsupervised learning, regression, decision trees, and classification.
SDLC frameworks, UML modeling, requirements gathering, and system design patterns.
Talent acquisition, performance metrics, team dynamics, and workforce leadership.
Dashboard creation, ETL processes, and tools like PowerBI and Tableau.
Full-stack introduction, RESTful services, web APIs, and client-server workflows.
Recommender systems, customer churn analysis, and marketing automation.
ERP architectures (SAP, Odoo), cross-functional integration, and inventory management.
Capital budgeting, risk analysis, financial modeling, and algorithmic trading basics.
Data pipelines, Hadoop/Spark ecosystems, and time-series forecasting.
Information security, regulatory compliance (GDPR/Data Privacy), and risk management.
Neural network architectures, sentiment analysis, LLMs, and chatbot implementation.
Competitive strategy analysis, business model design, and digital disruption.
AWS/Azure cloud services, microservices, containerization, and serverless design.
Optimization algorithms, route planning, and demand forecasting using AI.
Research paradigms, quantitative/qualitative methodologies, and hypothesis formulation.
Algorithmic bias, explainable AI (XAI), safety protocols, and socio-economic impacts.
Robotic Process Automation (RPA), workflow orchestration, and change management.
Scrum framework, product roadmaps, user stories, Sprint planning, and deployment.
Prompt engineering, generative models, multi-criteria decision models, and IDSS.
Startup financing, venture capital, intellectual property, and global market analysis.
An independent research project requiring students to design, develop, and evaluate an AI-driven business system or solve a complex analytical business problem under academic supervision.