School of Future

BCA in Applied AI & Data Analytics

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Programme Overview

The BCA in Applied AI & Data Analytics is a future-focused undergraduate program that blends the power of Artificial Intelligence, Machine Learning, and Data Analytics to equip students with the skills to transform data into actionable insights. Designed under a Work-Integrated Learning Model, the program bridges academic concepts with real-world industry applications, ensuring learners are job-ready from day one.

Students gain in-depth knowledge of AI algorithms, predictive analytics, big data tools, and visualization techniques, while also mastering the fundamentals of programming, databases, and business intelligence. The curriculum emphasizes hands-on learning through live projects, internships, and mentorship from industry professionals, allowing learners to apply AI and analytics techniques to real-world business and technology challenges. Graduates emerge as skilled professionals ready to take on roles such as Data Analyst, Machine Learning Engineer, AI Developer, and Business Intelligence Specialist, driving innovation and decision-making in data-driven organizations.

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Telephone

+91 92073 55555

enquiry.kochi@jainuniversity.ac.in

Program code

0000

Duration

03 Years

Study Campus

JAIN University, Kochi Campus

Curriculum Structure

Python Fundamentals & Data Structures

Computer Organization & Architecture

Statistical Methods for Data Science

Probability & Vector Spaces

Intro to Data Visualization

SQL & Database Design for Analytics

Advanced Python for Data Engineering (Pandas, NumPy)

Exploratory Data Analysis (Power BI / Tableau)

Programming Practices using Java

Responsible AI & Data Ethics Primer

Data Cleaning & Wrangling Techniques

Feature Engineering & Model Selection

Predictive Analytics & Evaluation Metrics

Industry Case Study – Forecasting and Trends

Machine Learning & Applied AI Models

Deep Learning Fundamentals (CNNs, RNNs)

Natural Language Processing Essentials

Visualization Dashboards for Decision Support

Big Data Processing (Hadoop, Spark)

Cloud Analytics (GCP, AWS)

MLOps Pipelines & Version Control

Project

Data Governance & AI Compliance

Ethical AI & Bias Evaluation

Capstone – AI-Driven Business Intelligence

Course Highlights

1. Real-World Datasets from Industry Partners

Work with authentic datasets provided by industry collaborators to gain practical experience in solving real business and technology challenges.

2. End-to-End Analytics Project Pipeline

Learn to manage the complete analytics lifecycle — from data collection and processing to model building, visualization, and insight generation.

3. Focus on Data Ethics and Responsible AI

Understand the ethical dimensions of AI and analytics, ensuring your solutions are transparent, fair, and socially responsible.

Career Outcomes

This specialization prepares students to transform data into intelligence and insight into impact. Graduates gain deep expertise in analytics, machine learning, and applied AI, enabling them to solve real-world problems using data-driven decision-making. They are equipped to work across domains such as business intelligence, finance, retail, and research, helping organizations predict trends, optimize processes, and innovate faster. With a strong foundation in data science tools and responsible AI practices, students become industry-ready professionals who can design predictive models, automate insights, and communicate analytics effectively to decision-makers driving growth and innovation in every sector where data powers progress.

Data Scientist

Data Analyst

BI Developer

ML Engineer

FAQs

Traditional AI centers on theory, while Applied AI focuses on deploying machine learning and deep learning models for real-world problems across industries, bridging research and application.

Data Analytics is central to AI decision-making. Students gain proficiency in gathering, cleaning, and interpreting data using tools like Python and SQL, turning raw information into actionable insights.

Internships, live projects, and mentorship enable students to directly apply their knowledge to real industry data and challenges, thereby building both technical and domain expertise before graduation.

Graduates pursue roles like AI Analyst, Data Scientist, and Machine Learning Engineer. Their combined AI skills and industry experience prepare them for finance, healthcare, and technology sectors.