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AAFT  > Programs  > Data Science  > Post Graduate  > M.Sc in Data Science

On-Campus : Delhi-NCR

M.Sc in Data Science Course

Master the Language of Data. Become Future-Ready in AI & Data Science.
  • Master Deep Learning & Neural Network Architectures
  • Design & Implement Real-World Data-Driven Systems
  • Exclusive Mentorship by Dipanjan Sarkar
  • Learn Ethical AI, Data Governance & Compliance
  • Industry-Driven Learning with an AI-Integrated Curriculum
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    M.Sc in Data Science Program Details

    Batch

    2026

    Duration

    2 Years

    Eligibility Criteria

    UG

    Course Mode

    5 Days a week

    M.Sc in Data Science Course Overview

    The M.Sc in Data Science is a structured, progression-based program designed to build strong conceptual, technical, and analytical foundations in data-driven thinking. The program begins with core data science principles, toolkits, and programming fundamentals, gradually introducing diverse data formats, analytical methods, and computational approaches. Throughout the AI data science course, students learn through a balanced mix of theory, hands-on labs, and applied coursework covering statistics, machine learning, big data technologies, and data ethics. As they advance, students engage in research methodologies, real-world data problem-solving, and guided specialization pathways aligned with industry domains.

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    Why Choose AAFT for M.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 at one of the best colleges for data science, 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

    • Work with Generative AI workflows
    • Create NLP & recommendation systems
    • Deploy intelligent data-driven solutions
    • 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

      Additional Features

    • AI-Powered SEO, SEM & Content Automation Training
    • Build Websites, Campaigns & Portfolios Using AI
    • Real-Time Analytics, E-Commerce & Performance Marketing Mastery
    AI Integrated Data Science Curriculum

    Learn Data Science for the AI Era

    At AAFT School of Data Science, students build strong foundations in data, statistics and machine learning — with hands-on exposure to the tools and frameworks shaping the modern AI industry.

    NLP & Text Processing NLTK, spaCy and Gensim for language understanding, entity recognition and text modelling
    LLM Frameworks LangChain and LlamaIndex for building language model pipelines and retrieval applications
    Vector Search & RAG Pinecone and FAISS for semantic search with RAG architectures for grounded AI outputs
    Generative AI Diffusion Models and DALL-E for AI image generation and multimodal AI exploration

    Future Data Science Pipeline

    1

    Collect & Process

    Data ingestion, text cleaning, tokenisation and corpus preparation with NLTK and spaCy.

    2

    Represent & Embed

    Word vectors, semantic embeddings, topic models and knowledge graph construction with Gensim.

    3

    Store & Retrieve

    Vector indexing, similarity search and scalable retrieval with Pinecone and FAISS.

    4

    Orchestrate & Generate

    LLM chaining, RAG workflows and intelligent agent design using LangChain and LlamaIndex.

    5

    Visualise & Deploy

    AI image generation, multimodal outputs and portfolio-ready intelligent system deployment.

    AI Tools Students Work With

    A curated set of tools spanning NLP, LLM frameworks, vector databases, retrieval systems and generative AI — used across B.Sc. and M.Sc. programs at AAFT School of Data Science.

    LLM Framework

    LangChain

    An open-source framework for building applications with large language models, supporting prompt chaining, agents and tool integration.

    Data Framework

    LlamaIndex

    A framework for connecting LLMs to external data sources through document indexing, querying and structured retrieval.

    Retrieval Method

    RAG

    Retrieval-Augmented Generation — a technique that combines document retrieval with language model generation for grounded AI responses.

    Vector Database

    Pinecone

    A managed vector database for storing and querying high-dimensional embeddings at scale, used in semantic search applications.

    Vector Search

    FAISS

    Facebook AI Similarity Search — an open-source library for efficient similarity search and clustering of dense vectors.

    NLP Library

    NLTK

    Natural Language Toolkit — a Python library for text processing including tokenisation, stemming, parsing and corpus access.

    NLP Library

    spaCy

    An industrial-strength NLP library for named entity recognition, dependency parsing, text classification and pipeline building.

    Text Modelling

    Gensim

    A Python library for topic modelling, document similarity and word embedding models including Word2Vec and Doc2Vec.

    Generative AI

    Diffusion Models

    A class of generative AI models that learn to produce images by reversing a noise process — the basis of modern AI image generation.

    Image Generation

    DALL-E

    OpenAI's text-to-image model that generates images from natural language prompts, used in multimodal AI exploration.

    AI-Integrated Curriculum

    AAFT vs Other Data Science Institutes

    AAFT's tool-integrated curriculum gives students hands-on exposure to the frameworks used in real data science and AI roles.

    Learning Area Other Institutes AAFT School of Data Science

    Build Your Data Science Career With the Right Tools

    AAFT's B.Sc. Data Science, B.Sc. Artificial Intelligence and M.Sc. Data Science programs give students hands-on exposure to the tools — LangChain, LlamaIndex, RAG, Pinecone, FAISS, NLTK, spaCy, Gensim, Diffusion Models and DALL-E — that matter in the modern data and AI industry.

    Talk to an Academic Counsellor Download Brochure

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

    The M.Sc in Data Science is designed for graduates who are keen to deepen their expertise in data-driven analysis, computational methods, and advanced problem-solving. It is well-suited for learners seeking structured postgraduate training in programming, statistics, machine learning, big data analytics, and research methodologies. The data analytics program also appeals to professionals from allied disciplines who wish to transition into advanced data science roles or strengthen their analytical and technical capabilities. Overall, the AI and data science course supports individuals aiming to build advanced data science competencies, specialize in emerging domains, and adapt to evolving industry demands across analytics, artificial intelligence, and data-centric technologies.


    Our Alumni Work at

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

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    M.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.

    aaft Unlock Your Data Science Career   

    Potential Career Opportunities after M.Sc in Data Science Course

  • Data Scientist
  • Data Analyst
  • NLP Expert
  • Data Engineer
  • Analytics Consultant
  • Decision Science Analyst
  • AI Business Analyst
  • Quantitative Analyst
  • Data Security Officer
  • Statistical Modeler
  • Operations Research Analyst
  • Product Analytics Manager
  • Machine Learning Engineer
  • Data Governance Analyst
  • Data Visualization Specialist
  • Marketing Analytics Specialist
  • Risk & Fraud Analytics Analyst
  • Business Intelligence (BI) Analyst
  • M.Sc in Data Science Course Curriculum Breakdown

    Semester 1 - Python Fundamentals & Business Intelligence
    Subject 1: Data Science Essentials
    Learn data handling, exploration, visualization, and reporting using Excel, gaining foundational data science concepts and preprocessing skills.
    Subject 2: Statistical Approaches
    Develop proficiency in probability, descriptive and inferential statistics, correlation, regression, and experimental design for data-driven decision making.
    Subject 3: Relational Databases
    Understand database design, relational models, SQL querying, and optimization techniques to manage and manipulate structured data efficiently.
    Subject 4: Business Intelligence
    Acquire skills in data collection, analysis, visualization, and dashboard creation to support strategic business decision-making with BI tools.
    Subject 5: Python Fundamentals
    Gain foundational Python programming skills and practical experience with libraries like Pandas, NumPy, and Matplotlib for data analysis.
    Semester 2 - Relational Databases
    Subject 1: Data Science Essentials
    Learn data handling, exploration, visualization, and reporting using Excel, gaining foundational data science concepts and preprocessing skills.
    Subject 2: Statistical Approaches
    Develop proficiency in probability, descriptive and inferential statistics, correlation, regression, and experimental design for data-driven decision making.
    Subject 3: Relational Databases
    Understand database design, relational models, SQL querying, and optimization techniques to manage and manipulate structured data efficiently.
    Subject 4: Business Intelligence
    Acquire skills in data collection, analysis, visualization, and dashboard creation to support strategic business decision-making with BI tools.
    Subject 5: Python Fundamentals
    Gain foundational Python programming skills and practical experience with libraries like Pandas, NumPy, and Matplotlib for data analysis.
    CARE Online Program
    Provides resources and training modules to build professional skills, self-awareness, and job-readiness through assessments, group discussions, and case studies.
    Summer Internship
    Undertake a mandatory 6–8 week credited internship to gain hands-on industry experience, professional exposure, and career-oriented practical skills.
    Semester 3 - Neural Network Models
    Subject 1: Neural Network Models
    Learn to design, train, and deploy neural networks, including CNNs, RNNs, and deep learning architectures for real-world applications.
    Subject 2: Text Analytics
    Acquire skills in NLP, text preprocessing, sentiment analysis, topic modeling, and classification to extract insights from unstructured data.
    Subject 3: MLOps
    Gain hands-on expertise in building, deploying, and optimizing end-to-end machine learning pipelines for scalable, production-ready models.
    Subject 4: Generative AI
    Develop proficiency in designing and implementing generative models to create images, text, music, and innovative data-driven outputs.
    EDGE / Professional Practice
    Introduces real-world industry practices, teamwork, deadlines, and project execution to bridge academic learning with professional workflows.
    Semester 4 - Data Collection & Preprocessing
    Subject 1: Data Collection & Preprocessing
    Learn to translate real-world problems into AI tasks, collect and preprocess data, ensuring quality for robust solutions.
    Subject 2: Exploratory Data Analysis & Feature Engineering
    Analyze datasets, identify patterns and anomalies, and create features to enhance machine learning model performance.
    Subject 3: Modelling & Evaluation
    Apply appropriate ML algorithms, train models, and evaluate performance using metrics for reliable predictive systems.
    Subject 4: Results & Analysis
    Interpret model outcomes, visualize results, and extract actionable insights to support informed decision-making.
    Subject 5 – Specialization (Choose any one)
    Option 1: Deployment/MLOps (Machine Learning)
    Build, optimize, and deploy end-to-end ML pipelines, ensuring scalable production-ready solutions and performance monitoring.
    Option 2: Deployment/MLOps (Artificial Intelligence)
    Develop and deploy LLM-based AI systems, optimize prompts, fine-tune models, and evaluate for real-world applications.
    Option 3: Deployment/MLOps (Business Intelligence)
    Leverage BI tools to analyze data, create dashboards, and generate insights for strategic, data-driven business decisions.
    Option 4: Deployment/MLOps (Cloud Technologies)
    Implement ML projects using AWS, Azure, and GCP, ensuring scalable, efficient, and cloud-based data solutions.
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    Tools You Will Master in M.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

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    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

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    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

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    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
  • M.Sc in Data Science Course Student Projects

    M.Sc in Data Science
    Sales and Profit Dashboard
    Student Work
    M.Sc in Data Science
    Blinkit Dashboard
    Student Work
    M.Sc in Data Science
    Sales Dashboard
    Student Work
    M.Sc in Data Science
    Blinkit Dashboard
    Student Work

    Placements Opportunities

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    Vansh Kumar
    Physicswalla
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    Komal Prakash
    Zipee
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    Ashish Manocha
    VLCC
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    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
    M.Sc in Data Science

    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.

    Read More

    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.

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    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.

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    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).

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    Mr. Abhishek Ananda

    Assistant Professor

    Mr. Abhishek Ananda is a distinguished Data Science researcher and expert with extensive experience spanning both academia and .... industry. He holds a B.E. in Electronics Engineering from Nagpur University and an M.Tech in VLSI Design from NIT Kurukshetra, and is currently pursuing his Ph.D. at VNIT Nagpur. With a strong foundation in Python, Computer Vision, Image Processing, and Data Science, he has developed and implemented data-driven solutions across various domains. His expertise lies in data extraction, machine learning, and advanced analytics, enabling organizations to transform raw data into actionable insights. Throughout his career, Mr. Ananda has successfully mentored aspiring data scientists, equipping them with essential skills to excel in the field. His teaching approach emphasizes both theoretical understanding and practical application, ensuring students gain hands-on experience with industry-relevant tools and techniques.

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    Mr. Dheeraj Panchal

    Assistant Professor

    Mr. Dheeraj Panchal, a B.Tech graduate in Mechanical Engineering, has over 3 years of experience in career counselling and .... education technology. He holds strong expertise in Artificial Intelligence, Machine Learning, and Data Science, with skills in Natural Language Processing (NLP), SQL, and predictive analytics. His teaching approach focuses on connecting core concepts with real-world applications, enabling students to grasp AI-driven problem-solving effectively. As an Assistant Professor, he is committed to guiding students toward success in emerging technologies.

    Read More

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    AAFT Campus and Infrastructure

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    Admission Eligibility & Fee Structure

    Fee Structure for M.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/-
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    Candidate must have a 10+2 from a recognized university/institution
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    Candidate must have a minimum of 50% marks in 10+2 (45% for reserved categories)
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    Candidate need to clear the AAFT Global Entrance Test (GET)
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    How to Apply for M.Sc in Data Science?

    M.Sc in Data Science
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    M.Sc in Data Science
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    M.Sc in Data Science
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    M.Sc in Data Science
    ------------------------
    M.Sc in Data Science
    M.Sc in Data Science

    Registration

    Fill out the form mentioned above.

    M.Sc in Data Science

    Personal Interaction

    Our experts will help find the perfect program for you.

    M.Sc in Data Science

    Application

    Submit the application form to initiate your enrollment.

    M.Sc in Data Science

    Reservation

    Submit the course fee to reserve your seat.

    M.Sc in Data Science

    Enrollment

    Finalize your enrollment to begin your creative journey.

    M.Sc in Data Science
    -----

    Registration

    Fill out the form mentioned above.

    M.Sc in Data Science
    -----

    Personal Interaction

    Our experts will help find the perfect program for you.

    M.Sc in Data Science
    -----

    Application

    Submit the application form to initiate your enrollment.

    M.Sc in Data Science
    -----

    Reservation

    Submit the course fee to reserve your seat.

    M.Sc in Data Science

    Enrollment

    Finalize your enrollment to begin your creative journey.

    M.Sc in Data Science FAQs

    What are the eligibility criteria for M.Sc Data Science at AAFT?

    Applicants in M.Sc Data Science at AAFT need to possess the following requirements:

    • Educational Qualification: The applicant should have finished graduation from a known university or institution.
    • Minimum Marks: At least 50% aggregate marks in graduation required (45% in case of reserved category) is necessary.
    • Entrance Test: In order to get admission in AAFT, applicants need to pass the AAFT Global Entrance Test (GET).

    These requirements guarantee that students possess the academic background and talent to be effective in the professional M.Sc Data Science at AAFT.

    Is AAFT considered one of the top colleges for M.Sc Data Science in India?

    Yes, AAFT is gaining popularity as one of the top institutions of M.Sc Data science India because of its industry-oriented curriculum and its exposure. The School of Data Science is a hardcore School that combines both academic and practical education. The advantages enjoyed by the students include modern laboratories, faculty expertise, and projects. Having well-defined career advancement options starting with the Diploma in Data Science and undergraduate degrees, AAFT is the center of attention of students who would like to have a structured and career-oriented master's program in data science.

    How does a Master's in Data Science boost career growth compared to a diploma?

    A Master's in Data Science has more academic foundation and leadership preparation than a short-term diploma. Key advantages include:

    • High-end machine learning and AI.
    • In-depth research and analysis.
    • Master's degree in data science, as recognized in the industry.
    • Senior positions and international assignments.

    A master's degree, compared to diplomas, develops strategic thinking, and graduates are suitable in occupations such as data scientist, AI analyst, and data strategy consultant.

    Does AAFT offer an online data science master's, or is it strictly on-campus?

    AAFT mostly provides the M.Sc Data Science through immersive on-campus learning with the help of digital tools. Although the institute combines elements of an online master's in data science, like cloud-based platforms, virtual databases, and remote learning, the underlying experience is based on practical work and faculty roles (through mentorship) and team projects. Such a combination will provide the students with the flexibility of online systems and the advantages of structured academic and peer interaction.

    What is the syllabus for the Data Science Master's Degree program?

    The AAFT data science master's degree syllabus is an industry-based and extensive program. Core areas include:

    • Statistics and probability
    • Python and R programming
    • Data visualization and data storytelling
    • Algorithms of machine learning
    • Big data frameworks
    • The basics of artificial intelligence
    • Capstone research projects

    This is a carefully designed curriculum whereby graduates are both technically skilled and analytically assured in a wide range of data science master's programs.

    Are Data Science Masters programs open to students from non-technical backgrounds?

    Yes, the master's data science programs of AAFT can accept students with a non-technical background and aptitude in analysis. The program starts with introductory courses bridging gaps in programming, mathematics, and statistics. Business, economics, management, or media graduates have a tendency to do well after the first orientation. This is inclusive, and therefore, learners who are motivated will be able to pursue an M.Sc Data Science India degree with no prior knowledge of coding.

    What is the fee structure for M.Sc Data Science at AAFT?

    Total tuition fee of M.Sc in Data Science program at AAFT Noida is around ₹3.32 Lakhs over the 2 year period. The overall investment is approximately ₹6.44 Lakhs, including other expenses like hostel charges. The fee system includes such elements as registration ( ₹20,000), confirmation ( ₹30,000), and enrollment fees.

    Does the M.Sc Data Science eligibility require a background in mathematics?

    A good background in mathematics is not compulsory, but desirable for the M.Sc. Data Science eligibility. The initial training in statistics and quantitative reasoning is offered by AAFT in the first semester. Simple numerical comfort and desire to learn can be successful in students. The strategy enables students with different academic backgrounds to start masters in data science with no fear of being constrained by their previous major.

    How does the AAFT Masters in Data Science prepare students for AI roles?

    Artificial intelligence is one of the essential pillars of learning in the Master's in Data Science at AAFT. Students gain exposure to:

    • Deep learning and machine learning
    • Neural networks
    • Predictive modeling
    • AI-driven decision systems
    • Data ethics and governance

    The course does not have any paths out of the B.Sc. in Artificial Intelligence, and allows graduates to take AI-related positions, including data analyst, AI engineer, and machine learning specialist.

    Do Data Science Masters programs at AAFT include industry capstone projects?

    Yes, every program of data science master's at AAFT has an industry-oriented capstone project. Students solve business, healthcare, finance, or media problems on actual datasets. These projects challenge critical thinking, the use of tools, and presentation skills. Capstones play a bigger role in enhancing portfolios and also assist in the gap between academia and practice in the M.Sc Data Science India framework.

    Is the Data Science Master Degree recognized internationally?

    The master's data science degree at AAFT is designed to address international academic and industrial standards. The curriculum is in line with international standards, tools, and methodologies of analytics. The graduates may work in multinational firms, distant international teams, or pursue post-graduate studies in foreign countries. This accolade will make the M.Sc Data Science applicable to the global labor markets and educational tracks.

    What tools are taught in the M.Sc Data Science India program (e.g., Tableau, R)?

    The M.Sc Data Science India course focuses on practical mastery of the tools. Students learn:

    • Python and R
    • Tableau and Power BI
    • SQL and NoSQL databases
    • Machine learning libraries
    • Analytics applications in the clouds

    A technical toolkit equips graduates with real-world skills in analytics and makes them employable in a variety of data science master's programs.

    Can working professionals apply for the online data science masters options?

    The M.Sc Data Science can be offered to working professionals because AAFT helps to lead a flexible lifestyle with the help of online materials and regular schedules. Although it is not the most distant, the program still brings some similarities to the models of msc data science online, namely the virtual labs and cloud tools. This enables it to be a viable option for career-advancing professionals who want to have an online masters level data science learning experience.

    What are the placement statistics for M.Sc Data Science graduates?

    AAFT has good placement support of graduate in M.Sc Data Science. Students are hired to work in positions such as:

    • Data analyst
    • Business intelligence expert
    • Machine learning associate
    • AI and analytics consultant

    The placement cell assists resume construction, interviews, and industry relationships, resulting in higher outcomes in masters in Data Science career tracks.

    Why choose AAFT for Data Science Masters programs over other institutes?

    AAFT is characterized by practice-driven masters of data science and a cross-functional ecosystem. The institute is a blend of academic rigour, industry exposure, and up-to-date infrastructure. AAFT has progression options of Diploma in Data Science and undergraduate programs, thereby providing continuity and career clarity. Its analytics and AI integration focus, as well as its real-world project, make it a good option when deciding to pursue an M.Sc Data Science degree in India.

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