Advanced Program in IndustrialData Science (APIDS)
with Generative AI & Agentic AI...

Transform Your Career into a High-Paying Data Science Role

The Advanced Program in Industrial Data Science is designed for graduates and working professionals who want to switch or accelerate their career in Data Science using Generative AI and Agentic AI.

This industry-oriented program equips you with job-ready, hands-on skills that are in high demand across India and global markets.

šŸ‘‰ Whether you come from IT, non-IT, analytics, finance, telecom, banking, or any other domain — this program is built for you.

Advanced Program in Industrial Data Science (APIDS)

The Advanced Program in Industrial Data Science (APIDS) with Generative AI & Agentic AI equips you with essential skills in database programming, reporting, data visualization, statistics, advanced analytics, and artificial intelligence. You will learn to analyze and visualize large datasets, identify patterns and trends, and present insights effectively through charts, dashboards, and reports.

The curriculum covers machine learning and AI techniques, including supervised and unsupervised learning, deep learning with Python, TensorFlow, and Keras, as well as reinforcement learning for building AI-driven solutions such as recommender systems. Additionally, you will explore generative AI techniques and cloud computing, enabling you to automate processes, uncover new data patterns, and develop AI-centric business solutions.

Why Choose This Program?

  • Career transition into high-paying Data Science & AI roles

  • Opportunities in India & Abroad

  • Strong focus on Gen AI & Agentic AI (future-proof skills)

  • Industrial & real-world use cases

  • End-to-end exposure: Data → Models → Deployment

  • Designed for working professionals & fresh graduates

Who Should Join?

  • Graduates (Any Stream)

  • Working Professionals (IT / Non-IT)

  • Software Engineers

  • Analysts (Banking, Finance, Telecom, Marketing, Risk, etc.)

  • Professionals planning a career switch to Data Science & AI

No prior Data Science experience required.
We start from the fundamentals and progress to advanced AI systems.

What you will learn in (APIDS)?

DBMS programming is essential for efficient data access, querying, and analysis. It
ensures data integrity and security, with techniques like indexing and optimization for
performance enhancement. Build strong data and programming foundations used in real industries:

  • SQL (Beginner to Advanced)

  • Python for Data Science

  • PySpark

  • Scala

Core skills for data scientists include data analysis and visualization, crucial for
extracting insights and communicating findings effectively. Techniques encompass
statistical analysis, machine learning, and exploratory data analysis (EDA). Learn how to analyze data and present insights to business stakeholders:

  • Excel (Basic & Advanced)

  • Excel with AI features

  • Tableau

  • Power BI

Data mining equips data scientists with tools to extract valuable insights from large
datasets. Techniques include pattern recognition, predictive modeling, classification,
clustering, and anomaly detection. Data scientists leverage these methods to uncover
hidden patterns, trends, and relationships, informing strategic decisions and driving
innovation:

  • Statistics for Machine Learning

  • Python Machine Learning

  • Python Deep Learning

  • Generative AI (LLMs, Prompting, Applications)

  • Agentic AI (Autonomous AI Agents & Workflows)

Data scientists benefit from cloud computing skills for scalable data processing and
analysis. Proficiency in major cloud platforms like AWS, Azure, and GCP is vital, alongside
big data frameworks such as Hadoop and Spark. Understanding containerization with
Docker and orchestration using Kubernetes ensures seamless deployment.
Become industry-ready with cloud and production-level skills:

  • Cloud-based Model Deployment

  • MLOps (Model Lifecycle Management)

  • LLMOps (Gen AI & Agent Deployment)

What Makes This Program Industrial?

  • āœ… Real-time datasets & case studies

  • āœ… Business-driven problem statements

  • āœ… End-to-end projects (Data → Model → Deployment)

  • āœ… Exposure to enterprise tools & cloud platforms

  • āœ… AI systems used by real companies

Career Outcomes

  • After completing this program, you can target roles such as:

    • Data Scientist

    • Machine Learning Engineer

    • AI Engineer

    • Gen AI Engineer

    • Analytics Consultant

    • Business Data Analyst

    šŸ’° High-paying roles with strong growth potential

Program Highlights

  • Structured learning from basics to advanced AI

  • Strong focus on Gen AI & Agentic AI

  • Hands-on projects & practical assignments

  • Cloud & deployment exposure

  • Industry-aligned curriculum

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    Ready to Secure Your AI Future?

    Data Science powered by Generative AI and Agentic AI is not the future — it is happening now.

    šŸ‘‰ Join the Advanced Program in Industrial Data Science and build a globally relevant, high-impact career.

    šŸŽÆ Limited Seats Available

    INDUSTRY REAL-TIME
    DATA SCIENCE PROJECTS

    Retail Marketing

    The world we live in is evolving every day. There are significant changes in the retail market as opposed to how it was a decade or two ago. With sales worth trillions of dollars worldwide, retail industry is expected to develop even further in the coming days. Data Analytics can be used in the retail industry for various reliable decisions. Be it customer retention or sales prediction, we can develop models using data to provide the best possible solutions.

    • Targeted customer communication
    • Price optimization
    • Demand prediction and inventory management
    • Customer experience enhancement
    • Market trend prediction
    • Customer retention
    • Strategic business decisions to increase sales

    Banking

    The remarkable variations that have happened in the banking industry over the past few years are not momentary. Many organizations are adapting to the latest trends in technology and are changing their business structure for enhanced security and the best customer experience. To make better business decisions, banks need to connect various data from both structured and unstructured sources. Banking analytics aids in providing valuable insights by gathering, processing, and analyzing data.

    • Customer identification and acquisition
    • Portfolio analysis and risk management
    • Customer retention
    • Credit risk analysis
    • Collection analysis
    • Marketing analysis

    Telecom

    Telecommunication industry has encountered extraordinary changes over the past few decades. From satellite internet to 5G services, the industry continues to grow together with the advancements in technology. With every company racing to get the best services delivered to each customer, it is challenging to gain a competitive advantage. Telecommunication data analytics (telecom analytics) can help solve your complex business problems by finding the most optimal solutions, using various statistical approaches such as data mining, data manipulation, descriptive modeling, or predictive modeling. We can discern and analyze the existing trends to find the most favorable outcome. Data analytics can help you save operational costs, maximize your profits, increase the sales, and even manage risks.

    • Targeted customer communication
    • Price optimization
    • Demand prediction and inventory management
    • Customer experience enhancement
    • Market trend prediction
    • Customer retention
    • Strategic business decisions to increase sales

    E-Commerce

    Ecommerce refers to trade that happens over the internet. Through online stores, it is possible to purchase a wide variety of products using your computer, tablet, smartphone, or other smart devices. Since ecommerce businesses exist in a virtual space, they need effective ecommerce analytics to predict the changes in the market. Ecommerce analytics can provide actionable insights on various aspects such as interaction of shoppers, online shopping trends, and common interests. Using statistical approaches, we can anticipate changes in the market, analyse risk, and make better business decisions.
    • Information analysis
    • Inventory forecasting
    • Customer experience analysis and targeted customer communication
    • Fraud prevention
    • Marketing analysis
    • Price optimization

    Healthcare

    Healthcare is a collective term for hospital services, medical devices, pharmaceutical services, insurance services, and any other medical care provisions provided for an individual or a community. It is said that prevention is always better than cure. While we cannot always prevent an event from occurring, we can always be prepared for its arrival. By gathering data, analyzing trends, and predicting possible outcomes, the application of Data Analytics in the healthcare industry are limitless. The insights that we obtain from healthcare data can support in making decisions that can have a significant business impact.
    • Risk Analysis
    • Insurance claim analysis
    • Operations analysis
    • Patient care analysis
    • Performance monitoring
    • Operational and interactive dashboards

    What requirement do you need?

    There are no prerequisites to attend this course online or ofline.
    Elementary programming knowledge will be of advantage.

    Training Supports & Benefits

    • Learn from the World’s Best Faculty & Industry Experts
    • Learn with fun Hands-on Exercises & Assignments
    • Participate in Hackathons & Group Activities
    • Dedicated Faculty
    • 9AM to 6 PM Support
    • Participate in Hackathons & Group Activities
    • Resume Building & Mock Interview Prep​aration.
    • We offer personalized access to our Learning Management System (LMS).
    • Moc Interview Practise + Real time Test

      Talk to an Expert





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