BSc Data Science Degree Course in Noida

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B.Sc in Data Science Program Details

Batch

2026

Duration

3 Years Degree

Eligibility Criteria

10+2/UG

Course Mode

5 Days a week

B.Sc in Data Science Course Overview

The B.Sc in Data Science is a future-ready undergraduate degree designed for students who aspire to understand, analyse, and solve real-world problems through data-driven approaches. The program introduces the fundamentals of data science, programming, statistics, and data ethics, and as learning advances, the curriculum takes students through the complete data lifecycle, starting from data collection, cleaning, and storage to analysis, visualisation, and predictive modelling, through subjects such as database systems, big data analytics, machine learning pipelines, and deep learning. The program emphasises hands-on learning through Python, machine learning, and deep learning labs, along with industry-oriented projects and research methodologies. Overall, industry exposure to diverse data formats and real-world datasets prepares students to work confidently across analytics, artificial intelligence, and emerging data-driven domains.

Why Choose AAFT for B.Sc in Data Science Course?

Step into a future-focused learning ecosystem designed to shape analytical thinkers and data-driven problem solvers. Explore the complete data science lifecycle, where numerical reasoning, computational logic, and statistical thinking become part of everyday learning. Study in lab-driven environments that mirror real industry workflows, guided by mentors who are active practitioners in data science and artificial intelligence. Every project, dataset, and industry engagement strengthens your analytical mindset, sharpens technical expertise, and builds solution-oriented thinking, preparing you to emerge as a confident, industry-ready data professional equipped to thrive in an evolving digital economy.

Key Highlights

Immersive, lab-centric learning for hands-on data mastery
Strong foundations in statistics, programming, and analytics
Structured progression from fundamentals to advanced data domains
Industry exposure through live projects and internships
Practical application of theory to real-world data problems
Capstone project demonstrating end-to-end data-driven solutions
Project-based learning with cross-school collaborative exposure

Additional Features

Enterprise-Grade Cloud & AI Infrastructure Access
Capstone Industry Projects with Research Integration
Production-Level MLOps & Scalable Deployment Training

Admissions Open 2026 - Apply Today

Who is this The B.Sc in Data Science Course for?

The B.Sc in Data Science is ideal for students who are passionate about working with data, technology, and analytical problem-solving. It is well-suited for learners seeking structured training in programming, statistics, data analysis, and machine learning fundamentals. The program also appeals to aspiring data analysts, technologists, and professionals from allied fields who wish to transition into data-driven roles or strengthen their analytical skill sets. Overall, the course supports individuals aiming to build strong data science foundations, advance analytical and computational skills, and adapt to evolving industry demands across analytics, artificial intelligence, and emerging data-centric domains.

Our Alumni Work at

Dedicated Career Resource Cell to help find your dream company with our partner recruiters across the globe.

B.Sc in Data Science Program Outcomes

Data Literacy Proficiency

Demonstrate a deep understanding of foundational data science concepts and principles, showcasing the ability to interpret and communicate complex data insights effectively across diverse audiences.

Comprehensive Data Analysis Skills

Develop proficiency in a range of data analysis techniques, including statistical analysis, machine learning, and predictive modeling, ensuring adaptability in addressing diverse data challenges within the evolving field of data science.

Ethical and Regulatory Awareness

Acquire a profound understanding of ethical considerations and regulatory frameworks in data science, fostering a commitment to responsible data handling, privacy protection, and compliance with legal standards.

Big Data Competency

Develop skills in handling and analyzing large-scale datasets, leveraging big data technologies, and understanding the challenges and opportunities presented by the era of big data.

Advanced Programming Competence

Master programming languages such as Python and R, gaining the skills required for data manipulation, analysis, and the development of robust data-driven applications.

Capstone Project Excellence

Apply data science skills to complete a comprehensive capstone project, demonstrating the ability to integrate knowledge from various areas and solve real-world problems through data-driven approaches.

Research and Innovation Capabilities

Cultivate innovative approaches to machine learning and artificial intelligence, enabling graduates to contribute to cutting-edge research, develop advanced models, and address complex real-world challenges.

Unlock Your Data Science Career

Potential Career Opportunities after B.Sc in Data Science Course

Data Scientist

Data Analyst

Machine Learning Engineer

Business Intelligence (BI) Analyst

Data Visualization Specialist

Analytics Consultant

Decision Science Analyst

AI Business Analyst

NLP Expert

Quantitative Analyst

Data Engineer

Data Security Officer

Statistical Modeler

Operations Research Analyst

Product Analytics Manager

Marketing Analytics Specialist

Risk & Fraud Analytics Analyst

Data Governance Analyst

B.Sc in Data Science Course Curriculum Breakdown

Semester 1 - Python Programming

Subject 1: Data Science Toolkits

Build foundational data science skills through data collection, cleaning, manipulation, visualization, and analysis using Python, NumPy, and Pandas.

Subject 2: Fundamentals of Programming

Develop core programming logic, problem-solving abilities, modular coding practices, and debugging skills for writing efficient, reusable software solutions.

Subject 3: Structured Query Language (SQL)

Learn database design, normalization, and query optimization while managing relational, NoSQL, and object-oriented databases using industry-standard systems.

Subject 4: Statistical Analytics

Apply statistical reasoning, critical thinking, and analytical problem-solving techniques to interpret data, communicate insights, and support decision-making.

Subject 5: Python Programming

Gain proficiency in Python programming, data structures, object-oriented concepts, file handling, and exception management for data-driven applications.

Semester 2 - Machine Learning Models

Subject 6: Data Structures using Python

Develop algorithmic problem-solving skills by implementing data structures, analyzing complexity, and designing efficient algorithms using Python.

Subject 7: Machine Learning Models

Build, train, and evaluate machine learning models using supervised, unsupervised techniques and libraries like scikit-learn.

Subject 8: Expert Python Programming

Master advanced Python concepts, concurrency, and design patterns to develop scalable, high-performance, and maintainable applications.

Subject 9: Unstructured Databases

Learn NoSQL database concepts and practical implementation for managing unstructured data in real-world data science applications.

Subject 10: Insight Analytics

Develop analytical and communication skills to interpret digital data, create insights, and design effective data-driven content strategies.

Semester 3 - Natural Language Processing

Subject 1: ML Pipelines

Design, implement, and optimize advanced machine learning pipelines using deep learning, reinforcement learning, and generative models.

Subject 2: Cloud Technology

Develop cloud-based solutions by deploying, managing, and scaling applications across AWS, Azure, and Google Cloud platforms.

Subject 3: Business Intelligence

Analyze organizational data and build interactive dashboards using BI tools to support strategic, data-driven decision-making.

Subject 4: Natural Language Processing

Build intelligent language-based systems by applying text processing, embeddings, transformers, and NLP algorithms to real-world data.

Subject 5: Neural Network Architectures

Implement and evaluate advanced neural network architectures for complex applications in computer vision, NLP, and autonomous systems.

CARE Online Program

Provides resources and training modules to build professional skills, self-awareness, and job-readiness through assessments, group discussions, and case studies.

Semester 4 - Big Data System

Subject 6: Big Data Systems

Develop expertise in big data mining, preprocessing, and data warehousing using industry-standard algorithms, tools, and performance evaluation techniques.

Subject 7: Computer Vision

Apply image processing and computer vision techniques to build, deploy, and evaluate real-world vision-based applications.

Subject 8: Deep Learning

Design, train, and evaluate deep learning models using TensorFlow or PyTorch for real-world intelligent applications.

Subject 9: Predictive Analytics

Build and evaluate predictive models using statistical methods and machine learning to solve real-world forecasting problems.

Subject 10: Neural Text Understanding

Develop neural network–based text analysis skills for sentiment analysis, classification, generation, and ethical NLP applications.

EDGE / Professional Practice

Introduces real-world industry practices, teamwork, deadlines, and project execution to bridge academic learning with professional workflows.

Summer Internship

Undertake a mandatory 6–8 week credited internship to gain hands-on industry experience, professional exposure, and career-oriented practical skills.

Semester 5 - Data Collection & Preprocessing

Subject 1: Data Collection & Preprocessing

Translate real-world problems into actionable AI tasks while designing scalable architectures for effective data and system integration.

Subject 2: Exploratory Data Analysis & Feature Engineering

Analyze, visualize, and engineer data features to uncover patterns, improve data quality, and enhance machine learning model performance.

Subject 3: Modelling & Evaluation

Select, train, and evaluate machine learning models using appropriate algorithms and metrics to build reliable predictive systems.

Subject 4: Results & Analysis

Interpret model outcomes through metrics and visualizations to generate actionable insights aligned with business and research objectives.

Subject 5: Deployment/MLOps (Choose Anyone)

Machine Learning

Build, deploy, monitor, and automate end-to-end machine learning workflows using MLOps practices, CI/CD pipelines, and performance monitoring.

Artificial Intelligence (LLMs)

Design, fine-tune, evaluate, and deploy large language models using prompt engineering, RAG techniques, and scalable production workflows.

Business Intelligence

Transform organizational data into actionable insights using data warehousing, analytics, and interactive dashboards for strategic decision-making.

Cloud Technologies

Develop and deploy scalable machine learning solutions using AWS, Azure, and GCP for efficient, secure, cloud-based workflows.

EDGE / Professional Practice

Introduces real-world industry practices, teamwork, deadlines, and project execution to bridge academic learning with professional workflows.

Semester 6 - Portfolio Development

Industry Internship

Gain hands-on industry experience through mentored projects, applying academic knowledge to real-world challenges and professional workflows.

Book Free Career Counselling

Tools You Will Master in B.Sc in Data Science Program at AAFT

1. Data Analysis & Programming Frameworks

Core tools used to collect, clean, analyze, and visualize structured and unstructured data efficiently. Includes: Python, R, NumPy, Pandas, Matplotlib, Seaborn, Jupyter Notebook, SQL, Excel

Industry applications:

Data analysis and reporting across industries

Business intelligence and decision support systems

Data-driven product and market analysis

Financial and risk analytics

Academic and applied research projects

Operational and performance analytics

Exploratory data analysis for machine learning projects

2. Machine Learning & Artificial Intelligence Tools

Technologies used to build, train, evaluate, and deploy predictive and intelligent data-driven models. Includes: Scikit-learn, TensorFlow, PyTorch, Keras, XGBoost, OpenCV, NLP libraries

Industry applications:

Predictive modeling and forecasting solutions

Recommendation systems and personalization engines

Computer vision and image analytics

Natural language processing applications

Fraud detection and anomaly detection

AI-powered automation systems

Intelligent decision-support platforms

3. Big Data, Cloud & Deployment Technologies

Platforms and tools used to manage large-scale data, deploy models, and enable scalable data solutions. Includes: Hadoop, Spark, MongoDB, AWS, Azure, Google Cloud Platform, Docker, Tableau, Power BI

Industry applications:

Big data processing and analytics pipelines

Cloud-based data science and AI deployments

Business dashboards and data visualization systems

Enterprise data warehousing solutions

Scalable machine learning model deployment

Real-time data streaming and analytics

Data-driven enterprise applications

B.Sc in Data Science Course Student Projects

Sales and Profit Dashboard

Student Work

Blinkit Dashboard

Student Work

Sales Dashboard

Student Work

Blinkit Dashboard

Student Work

Placements Opportunities

Vansh Kumar

Physicswalla

Komal Prakash

Zipee

Ashish Manocha

VLCC

Abhay Kumar

KPMG

Industry Dean

Dipanjan Sarkar

Dipanjan Sarkar brings over a decade of hands-on and leadership experience in Data Science and Artificial Intelligence, spanning industry, training, consulting, and education initiatives worldwide. He has led data teams and built end-to-end data products across Fortune 100 companies as well as startups. A published author, Google Developer Expert, and Cloud Champion Innovator, DJ has also played a key role in developing some of the world’s earliest end-to-end Generative AI training programs. Passionate about teaching, he enjoys sharing real-world insights and practical knowledge to support others on their AI learning journey.

Industry Dean

Dipanjan Sarkar

What this means for you

Access to 50+ hours of in-person learning
10 Masterclasses to expand your creative horizon

Exclusive internship and placement opportunities
Portfolio review from Dipanjan Sarkar and team

Veteran Teaching Faculty

AAFT boasts of a highly qualified and experienced team of professors who hold impeccable industrial acumen after having led successful careers in their respective fields.

Mr. Ashish Garg

Dean

An Educator and Technology Evangelist with over 25 years of experience in Professional Skill Development for Animation, VFX, .... Game Design, Game Development, Real-Time 3D Content Creation, Virtual Production, AR/VR Development, Metaverse, and Immersive Experience Design. Key skill areas include Leadership & Development, Project Management, Team Management, Creative Learning & Training, Professional Skill Development, Technical Education & Training, Innovative Curriculum & Courseware Design, and Education & Technology Integration.

Mr. Nitish Patil

Assistant Professor

B.Tech, M.Tech in Computer Science & Engineering with specialization in Data Science & Cloud Computing. Over 12 years of .... experience in academics, industry, and project development, focusing on data science, data visualization, database development, and cloud computing. Published 11 research papers in data mining, web mining, and AI, and holds a patent in “Clinical Decision Support System using Artificial Intelligence.” Certified in Oracle, MongoDB, Python (University of Michigan), and Dataiku, and experienced with Tableau and Power BI. Research interests include machine learning (logistic, KNN, SVM, K-means), deep learning (CNN, LSTM, RNN), NLP, computer vision, and MLOps.

Ms. Neema Jha

Assistant Professor

Executive postgraduate in data science with specialization in business intelligence & data analytics from IIIT Bangalore and M..... Tech from GGSIPU Delhi. Over 6 years of academic experience, skilled in SQL, Python, C++, Tableau, Power BI, Excel, and applying machine learning & AI to analytical challenges. Experienced with Big Data tools like Hadoop, Sqoop, and Hive. Research includes the synthesis and growth of semi-organic single crystals and their characterization for optical applications.

Mr. Gaurav Kumar

Assistant Professor

Accomplished data science professional with expertise in data extraction, business intelligence, and analytics, bridging both .... academia and industry. Has mentored students in real-world applications of data science and driven business solutions using data-driven insights. Certifications include Bloomberg Market Concepts (BMC), Google Data Analytics Professional Certificate, Generative AI, AWS, and currently pursuing Microsoft Certified Trainer (MCT).

Latest Software

High-End Computer System

Digital Class-Rooms

Admission Eligibility & Fee Structure

Fee Structure for B.Sc in Data Science
Actual fees for per Semester*	INR-100,000/-
Your 1st Installment Fees Includes the Following*
One Time Admission Fee	Rs. 30,000/-
One Time University Enrolment Fee	Rs. 2,200/-

Candidate must have a 10+2 from a recognized university/institution

Candidate must have a minimum of 50% marks in 10+2 (45% for reserved categories)

Candidate need to clear the AAFT Global Entrance Test (GET)

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How to Apply for B.Sc in Data Science?

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Registration

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Reservation

Submit the course fee to reserve your seat.

Enrollment

Finalize your enrollment to begin your creative journey.

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Registration

Fill out the form mentioned above.

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Personal Interaction

Our experts will help find the perfect program for you.

-----

Application

Submit the application form to initiate your enrollment.

-----

Reservation

Submit the course fee to reserve your seat.

Enrollment

Finalize your enrollment to begin your creative journey.

B.Sc in Data Science FAQs

Why choose a B.Sc in Data Science over a short certification?

A B.Sc in Data Science offers both full-scale academic and practical training in contrast to a short course in data science certification.

Key advantages include:

Proficiency in statistics, computer programming, and analytics.
Credibility and recognition of a career in the long term.
Government jobs and higher studies.
Presentation on AI-based concepts of data science.

The program provides long-term career development as the program at the School of Data Science at AAFT is correlated with further degrees, including M.Sc in Data Science.

Is the B.Sc in Data Science available as a data science course after 12th?

Yes, B.Sc in Data Science is a full course in data science given after 12 th. It is suitable for:

Students of the science stream, which includes math.
Trade undergraduates who are analytical.
Novices who want an organized data science education.

Basic courses will make sure that students develop technical skills gradually. There are also other alternatives, such as a Diploma in Data Science proposed by AAFT, in case students have shorter academic obligations.

What is the data science course duration for the B.Sc program?

The B.Sc program in data science lasts three years, consisting of six semesters. Such a well-organized time will enable the students to advance from the level of basic to advanced analytics and AI programs. The curriculum offered at AAFT has a balance between theory, laboratory work, and projects to make sure that the competence is a real course. The long-term nature allows closer learning of the subject and increased industry readiness, in comparison to the short-term programs.

Does AAFT offer the best data science course in Delhi?

AAFT is considered one of the best schools that provide a data science course in Delhi with own School of Data Science.

Key strengths include:

Industry-aligned curriculum
Well-trained academic and industry faculty.
Practical learning using actual data.

These aspects make AAFT a good option among the students who want to pursue data science education that is career oriented.

How does the AI and data science course curriculum prepare students for the future?

The AI and data science curriculum of AAFT is meant to accommodate the new needs in the industry. The curriculum focuses on:

Machine learning and predictive analytics.
Data-driven problem solving
Responsible and ethical implementation of AIs.
Relevant platforms and tools in the industry.

This future-oriented mechanism equips the students to perform in the changing positions within the technology-oriented industries.

What are the data science course fees and duration at AAFT?

In Noida, AAFT (Asian Academy of Film and Television) has data science courses with different costs and terms: a 3-year B.Sc. in Data Science is estimated at ₹4.32 Lakhs- ₹4.82 Lakhs, and a 1-year Diploma in Data Science will cost ₹1.20 Lakhs - ₹1.31 Lakhs.

Is a Bachelor of Science in Data Science recognized for government jobs?

Yes, a Bachelor of Science in Data Science is an accepted undergraduate degree, which means that those who have it can work in many governmental and public-service positions. The analytical and technical expertise gained in the course of the program is essential in the role within the research, IT, and data analytics departments. Also, the degree qualifies one to take competitive exams and graduate studies, such as advancing to M.Sc in Data Science, which further enhances employment opportunities in the long run.

Does the B.Sc in Data Science include a data science certification course?

The B.Sc in Data Science incorporates practical modules that are similar to a data science certification course into the degree program.

Students benefit from:

Industry-relevant skill-based learning.
In-curriculum certification-type tests.
Works that confirm real-life knowledge.
Professional contact with data science tools.

The combination of the two approaches will provide graduates with both depth in academics and job-readiness.

Can commerce students apply for the data science course after 12th?

Yes, the course in data science may be taken by the commerce students upon completing 12 th, provided that they meet eligibility requirements. AAFT grants first-year assistance in mathematics, statistics, and programming to allow students who are not in science to adjust. This makes the program accessible to commerce students with a strong analytical interest to successfully enter data science careers because of this inclusive approach.

What makes the AI and data science course at AAFT unique?

The academic design of the AI and data science course at AAFT is unique, as the course is integrated into the industry.

Unique features include:

High emphasis on applied analytics and AI.
Case-study and project-based learning.
University advancement to M.Sc Data Science.

This system makes sure that students are ready to take both technical and high-level courses.

How much practical coding is involved in the B.Sc in Data Science?

The B.Sc in Data Science curriculum has practical coding as a fundamental element. The students are constantly introduced to Python, R, and SQL in the lab sessions and assignments. The coding exercises are directed towards data cleaning, visualization, statistical analysis and model building. The constant practice will help the students have practical technical confidence in the field that differentiates the program among the theory-based intensive but short programs in data science.

Is AAFT the right place for a data science course in Delhi with placement?

AAFT provides good academic assistance and exposure to industry among students who have chosen to study a data science course in Delhi.

The placement-related assistance consists of:

Project work oriented on industry.
Portfolio development and career guidance.
Internship assistance
Skills training seminars.

Such programs contribute to the students being employment-fit and competitive in the analytics and data science employment market.

What is the difference between B.Tech and Bachelor of Science in Data Science?

The major distinction between the B.Tech and the Bachelor of Science in Data Science is academic focus. A B.Tech focuses on engineering and system-level development, whereas a B.Sc in Data Science is more oriented on analytics, statistics and AI-driven insights. The B.Sc degree is best suited to students who are willing to work in the data interpretation, decision-making and predictive modeling fields as opposed to traditional engineering.

Does the B.Sc program cover Python and R programming?

Yes, a B.Sc. in Data Science has both Python and R programs as its core subjects. Python is applicable in data analysis, machine learning, and automation, and R is utilized in statistical modeling and visualization. Lab sessions and projects allow students to use these languages practically, which guarantees practical proficiency in accordance with the requirements of the industry and highly developed analytics processes.

How can I apply for the B.Sc in Data Science at AAFT?

The B.Sc in Data Science offered by AAFT may be applied to by students using the official process of admission.

The process of application normally involves:

Academic documents submission.
Post 12 th eligibility conditions.
Guidance and counseling for admission.
Confirmation of final enrollment.

Other similar programs that applicants can consider in counseling include a Diploma in Data Science, B.Sc in Artificial Intelligence, or M.Sc in Data Science.

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B.Sc in Data Science

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B.Sc in Data Science

B.Sc in Data Science Program Details

B.Sc in Data Science Course Overview

Why Choose AAFT for B.Sc in Data Science Course?

Key Highlights

Additional Features

Who is this The B.Sc in Data Science Course for?

Our Alumni Work at

B.Sc in Data Science Program Outcomes

Potential Career Opportunities after B.Sc in Data Science Course

B.Sc in Data Science Course Curriculum Breakdown

Tools You Will Master in B.Sc in Data Science Program at AAFT

B.Sc in Data Science Course Student Projects

Placements Opportunities

What this means for you

Veteran Teaching Faculty

AAFT Campus and Infrastructure

Admission Eligibility & Fee Structure

How to Apply for B.Sc in Data Science?

Registration

Personal Interaction

Application

Reservation

Enrollment

B.Sc in Data Science FAQs

Related Courses

B.Sc. in Data Science Related Blogs