Master of Computer Application on Artificial Intelligence and Deep Learning

(In Collaboration with IBM)

2 Years Master Degree Programme

Our Apporach

Global Education, Global Acceptance

  • Our programs offer education with universal acceptance, providing students with a globally recognized standard.
  • State-of-the-art teaching and friendly mentoring are complemented by systematic workshops armed with pioneering technology.
  • We inspire motivation towards innovation and entrepreneurship, guiding students to create sustainable solutions for societal needs.

Industry-Academia Collaboration

Specialization

Programme Specialization

  • Artificial Intelligence and Deep Learning

Programme Details

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2 Years Programme

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Upto 100% Scholarship

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100% Placement Assistance

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Eligibility

The MCA with IBM program is meticulously crafted to equip students with a thorough comprehension of computer applications and business processes, accompanied by specialized training in IBM technologies. This program seamlessly integrates theoretical knowledge with hands-on skills, strategically preparing students for prosperous careers in the dynamic IT industry. The curriculum spans diverse subjects such as software development, database management, system analysis, and the seamless integration of cutting-edge IBM technologies. Through practical exposure to IBM tools and platforms, students emerge well-prepared to meet the ever-evolving demands of the IT sector.

  • Graduates will demonstrate a high level of technical competence in computer science and IBM technologies.
  • Students will exhibit the ability to analyze and solve complex problems related to IT and business processes.
  • The program instills a commitment to lifelong learning, preparing graduates to adapt to emerging technologies and industry trends.

  • Computational Proficiency:Apply computing, IBM technologies, and mathematics for real-world problem-solving.
  • Problem Analysis and Solution Formulation: Identify and solve complex problems, emphasizing adept analysis.
  • Solution Design and Evaluation:Design, evaluate solutions, aligning with IBM technologies for societal needs.
  • Research-based Investigations: Use research for investigations, ensuring valid conclusions in complex computing.
  • Modern Tool Proficiency:Apply contemporary techniques, including IBM tools, understanding limitations.
  • Professional Ethics and Computing Practices: Commit to IBM-specific ethics and computing norms.
  • Environmental and Societal Impact:Understand IBM's impact, emphasizing sustainability in computing solutions.
  • Project and Financial Management: Apply software engineering, project management, and financial principles in IBM projects

  • Graduates will excel in utilizing a diverse range of IBM tools for software development, data management, system integration, as well as specialized tools for AI and deep learning applications.
  • Students will adeptly design, develop, and deploy applications, with a particular emphasis on harnessing IBM technologies, including AI and deep learning frameworks.
  • The program prioritizes equipping students with advanced proficiency in database management, emphasizing expertise in IBM database solutions, particularly those integral to AI and deep learning applications.

Curriculum Details

Year wise Course Details

Odd Semester

Courses for this semester

Course Overview

The primary objective of this course is to offer an introductory level understanding of programming principles and the Python language. Students will be familiarized with core concepts such as data structures, conditionals, loops, variables, and functions. The course not only provides an overview of the tools utilized for Python development and execution but also ensures swift engagement in coding activities. Furthermore, students will have the opportunity to enhance their practical skills through hands-on coding exercises that involve commonly employed data structures, creating custom functions, and performing file input/output operations. In comparison to other introductory Python courses, this course offers a more comprehensive exploration of vital programming topics, providing a more in-depth learning experience.

Course Outcomes

  • Understand fundamental Python concepts, such as version distinctions, environment setup, and basic programming skills
  • Apply conditional execution and iteration in Python, demonstrating a grasp of fundamental control flow concepts
  • Understand and apply various types of Python functions
  • Apply Python's data structures, showcasing practical application skills and achieving proficiency in manipulating diverse data formats
  • Comprehend and apply object-oriented programming principles in Python, demonstrating the ability to design and implement modular and scalable software solutions

Course Overview

From the Web Technology unit in the course, students will learn to create more dynamic and interactive websites using JavaScript. Advanced HTML, CSS and basic JavaScript enhance the client-side web pages and students will learn to use these technologies for their specific purposes. Students begin working with server-side scripting and web applications development using PHP and MySQL in the second quarter. This will allow students to create websites that store, access, and use data stored in the database tables and it allows them to perform simple SQL queries to produce the desired results.

Course Outcomes

  • Understand the fundamentals of web application development, including client-side and server-side technologies.
  • Create web pages using HTML , Cascading Style Sheets ,JavaScript and XML
  • Develop dynamic web applications using server-side programming languages and frameworks such as PHP, Python
  • Implement data storage and retrieval in web applications using databases like MySQL
  • Understand basic of Internet

Course Overview

This is a foundation course that provides students with the mathematical knowledge and skills necessary to succeed in the MCA program. The course covers a wide range of topics, including algebra, logic, discrete mathematics, linear equations and matrices. Students will learn how to solve mathematical problems, apply mathematical concepts to real-world problems, and use this knowledge to enhance their understanding of other computer science topics.

Course Outcomes

  • Students will be able to understand and use the principles of mathematical reasoning to solve real-world problems.
  • Students will be able to use the appropriate maths skills and techniques in the analysis of data
  • Students will be able to interpret the results of mathematical computations and make contributions to their field.
  • Students will be able to distinguish between different types of equations and apply the appropriate one in order to solve a given problem.
  • Students will learn the basics of linear programming and will be able to apply it in solving optimisation problems

Course Overview

This course is designed to impart knowledge on the concepts of fundamental properties of probability and Statistics, distributions, testing of hypothesis for small and large samples in engineering applications.

Course Outcomes

  • Understanding the fundamental concepts of probability and statistics.
  • Describe important probability distributions like Binomial, Poisson Distributions and Normal Distributions.
  • Explain the concept of testing of hypothesis.
  • Analyse the concepts of correlation, regression and estimations and their properties.

Course Overview

In this course students will understand different data structures and how to use them effectively for solving problems. It is expected that the students have basic experience in any high-level programming language. Programming and Data Structures are a crucial part of programming interviews. This course is a complete course on complete data structure and algorithms. The main focus here will be mastering the Data structures; implementing those and some problems explaining application of those data structures and understand different programming paradigms, analysis of algorithms and applying different data structures.

Course Outcomes

  • Understand the fundamental concepts and principles of data structures
  • Use and implement appropriate data structure for the required problems using a programming language such as C.
  • Implement various data structures viz. Stacks, Queues, Linked Lists, Trees and Graphs.
  • Understand various searching & sorting techniques.
  • Apply an algorithm to write Selection Sort, Bubble Sort, Insertion Sort, Quick Sort, Merge Sort, Heap Sort and compare their performance in term of Space and Time complexity.

Course Overview

This course provides students with an in-depth understanding of data visualization techniques and tools commonly used in IT applications. Students will learn to use R programming and Python for data analysis and visualization, explore data visualization libraries such as ggplot2 and Matplotlib, and gain practical experience with interactive visualization tools like Tableau or Cognos. The course will also cover principles of effective data presentation and storytelling, and students will apply their skills to solve real-world IT problems through hands-on projects and case studies.

Course Outcomes

  • Understand the importance of data visualization in IT applications and its role in decision-making processes.
  • Demonstrate proficiency in using R programming and Python for data analysis and visualization tasks.
  • Utilize data visualization libraries like ggplot2 (R) and Matplotlib (Python) to create customized visualizations.
  • Design clear and persuasive visualizations using principles of effective data presentation and storytelling.
  • Utilize interactive data visualization tools like Cognos to create dynamic visualizations.
  • Understand the importance of data visualization in IT applications and its role in decision-making processes.
  • Demonstrate proficiency in using R programming and Python for data analysis and visualization tasks.
  • Utilize data visualization libraries like ggplot2 (R) and Matplotlib (Python) to create customized visualizations.
  • Design clear and persuasive visualizations using principles of effective data presentation and storytelling.
  • Utilize interactive data visualization tools like Cognos to create dynamic visualizations.
  • Understand the importance of data visualization in IT applications and its role in decision-making processes.
  • Demonstrate proficiency in using R programming and Python for data analysis and visualization tasks.
  • Utilize data visualization libraries like ggplot2 (R) and Matplotlib (Python) to create customized visualizations.
  • Design clear and persuasive visualizations using principles of effective data presentation and storytelling.
  • Utilize interactive data visualization tools like Cognos to create dynamic visualizations.
  • Understand the importance of data visualization in IT applications and its role in decision-making processes.
  • Demonstrate proficiency in using R programming and Python for data analysis and visualization tasks.
  • Utilize data visualization libraries like ggplot2 (R) and Matplotlib (Python) to create customized visualizations.
  • Design clear and persuasive visualizations using principles of effective data presentation and storytelling.
  • Utilize interactive data visualization tools like Cognos to create dynamic visualizations.
  • Understand the importance of data visualization in IT applications and its role in decision-making processes.
  • Demonstrate proficiency in using R programming and Python for data analysis and visualization tasks.
  • Utilize data visualization libraries like ggplot2 (R) and Matplotlib (Python) to create customized visualizations.
  • Design clear and persuasive visualizations using principles of effective data presentation and storytelling.
  • Utilize interactive data visualization tools like Cognos to create dynamic visualizations.
  • Understand the importance of data visualization in IT applications and its role in decision-making processes.
  • Demonstrate proficiency in using R programming and Python for data analysis and visualization tasks.
  • Utilize data visualization libraries like ggplot2 (R) and Matplotlib (Python) to create customized visualizations.
  • Design clear and persuasive visualizations using principles of effective data presentation and storytelling.
  • Utilize interactive data visualization tools like Cognos to create dynamic visualizations.
  • Understand the importance of data visualization in IT applications and its role in decision-making processes.
  • Demonstrate proficiency in using R programming and Python for data analysis and visualization tasks.
  • Utilize data visualization libraries like ggplot2 (R) and Matplotlib (Python) to create customized visualizations.
  • Design clear and persuasive visualizations using principles of effective data presentation and storytelling.
  • Utilize interactive data visualization tools like Cognos to create dynamic visualizations.

Course Overview

This course offers a comprehensive exploration of the foundational principles of Graph Theory, aiming to equip students with a deep understanding of graph structures and their applications. Covering key concepts such as graph representation, connectivity, algorithms, and coloring, students will develop both theoretical insights and practical problem-solving skills essential for analyzing complex systems across diverse disciplines.

Course Outcomes

  • Identify, describe, and utilize fundamental concepts of graph theory, including vertices, edges, paths, cycles, and different types of graphs like directed and undirected graphs.
  • Proficiency in representing graphs using various methods such as adjacency matrices, adjacency lists, and incidence matrices.
  • Develop the ability to implement and analyze key algorithms in graph theory
  • Develop the ability to implement and analyze key algorithms in graph theory
  • Explore graph coloring problems, understand their applications, and apply optimization techniques to solve real-world problems involving scheduling, resource allocation, and network designs.

Course Overview

This course focuses on the basics of algorithmic thinking and problem-solving techniques. Students will learn the foundational knowledge and skills in programming and algorithmic thinking.

Course Outcomes

  • Understanding of algorithms and their significance in problem-solving across various domains
  • Understanding of computational thinking and programming
  • Implement and analyze computational thinking different computational problems
  • Apply various algorithmic solutions to real world problems
  • Implementing problem decomposition and representation
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Even Semester

Courses for this semester

Course Overview

This course introduces to a variety of algorithms, approaches to algorithm design, and how they are effectively applied to solve problems in computer science. This course provides material that is more advanced and, in more depth, than an undergraduate data structures course, with a focus on algorithms and analysis. Topics include analysis and design of dynamic programs, greedy algorithms, numerical issues, randomization and NP-Completeness

Course Outcomes

  • Understand the fundamental concepts and principles of data structures
  • Understanding of advanced data structures such as balanced search trees (AVL, Red-Black trees), heaps, graphs, and hash tables.
  • Develop problem-solving skills by applying advanced data structures to solve complex programming problems efficiently
  • Understand how to analyze the efficiency and performance of algorithms that utilize advanced data structures
  • Ability to apply and implement learned algorithm design techniques and data structures to solve problems

Course Overview

Database management system is intended to provide a clear understanding of fundamentals with emphasis on their applications to create and manage large data sets. It emphasizes on technical overview of database software to retrieve data from database. This includes database design principles, normalization, and concurrent transaction processing, security, recovery and file organization techniques. This will provide adequate knowledge to understand future evolutions of data technologies.

Course Outcomes

  • Understand core database concepts, including data, information, metadata, and components of a Database Management System
  • Understand and apply various data modelling concepts
  • Understand and apply relational database concepts, relational algebra and SQL
  • Implement various normalization techniques ensuring efficient data organization
  • Understand the concepts of deadlocks, database security and distributed database systems

Course Overview

This course examines the important problems in operating system design and implementation. The operating system provides an established, convenient, and efficient interface between user programs and the bare hardware of the computer on which they run.

Course Outcomes

  • Understand the concepts of OS, the basic principles used in the design of modern operating system and process.
  • Understanding the concepts of processes, process scheduling including Throughput, Turnaround Time, Waiting Time, Response Time.
  • Understand the concepts of threads and mechanisms for synchronization.
  • Understand the concepts related to deadlock and memory management.
  • Understand the concepts of virtual memory management, file system.

Course Overview

The course is designed to provide students with a comprehensive understanding of the R programming language and its applications in data analysis and statistical computing. Throughout the course, students will learn the fundamentals of R programming, data manipulation and analysis, data visualization, and statistical modeling. By the end of the course, students will have a strong foundation in R programming, enabling them to confidently handle data manipulation, analysis, and visualization tasks. They will be equipped with the skills necessary to apply statistical techniques using R and effectively communicate their findings through visualizations and reports.

Course Outcomes

  • Understand R language and R studio
  • Analyze the use of basic functions of R Package
  • Create reports using R markdown
  • Implement statistical modeling using R
  • Demonstrate exploratory data analysis (EDA) for a given data set

Course Overview

This course is designed to emphasize the foundational methods and techniques of research in business management context. Students will be exposed to the main components of the research process i.e., research problem, research question, research objectives, research hypotheses, data collection, ethical issues in research, report writing, and presentation. The main objective of this course is to enable students to understand the research process and conduct research project in an area of their choice.

Course Outcomes

  • Understand the basic knowledge of Research methods
  • Understand the knowledge of Research Methodology
  • Understand the Skill of questionnaire development
  • Implement the acquired the knowledge to prepare the basic report/dissertation
  • Apply different statistical methods for finding the ideation of the problem

Course Overview

This course offers a comprehensive introduction to Cloud Computing, focusing on both theoretical concepts and practical applications. Students will learn about cloud models, services, and deployment models, with a specific focus on IBM Cloud resources. Topics covered include DevOps practices, RESTful APIs, containerization, and cloud-native development with Python. Through lectures, hands-on labs, and projects, students will gain practical experience in developing and deploying cloud applications.

Course Outcomes

  • Understanding of Cloud Computing Fundamentals
  • Proficiency in IBM Cloud Technologies
  • Competence in DevOps Practices
  • Skills in Cloud-Native Development with Python
  • Mastery of Containerization Technologies

Course Overview

This course provides a comprehensive overview of Discrete Mathematics, covering topics such as set theory, logic, combinatorics, relations, functions. Through theoretical exploration and practical applications, students develop problem-solving skills crucial for fields like computer science and engineering, preparing them for real-world challenges.

Course Outcomes

  • Understand and apply set theory and logic to form and evaluate logical arguments and mathematical proofs.
  • Master combinatorial techniques for solving counting problems relevant to algorithm design and data analysis.
  • Analyze and construct various types of relations and functions to develop a deeper understanding of algorithm efficiency and data structures.
  • Apply discrete mathematical concepts to solve practical problems in computer science, engineering, and related fields.
  • Develop advanced problem-solving skills to systematically approach and solve complex mathematical and real-world problems.

Course Overview

This course offers a foundational understanding of Mathematics tailored for basic programming with the C language. Covering essential mathematical concepts such as arithmetic operations, algebraic expressions, logic, and numerical computation, students gain the necessary skills to apply mathematical principles in programming tasks. Through practical exercises and programming assignments, this course equips students with the mathematical knowledge needed to solve problems efficiently and write robust C programs.

Course Outcomes

  • Master arithmetic operations and algebraic expressions to support efficient problem-solving in programming.
  • Understand and apply fundamental logical principles to develop sound algorithms and program flow in C.
  • Gain proficiency in numerical computation techniques essential for implementing complex mathematical functions in C programs.
  • Apply mathematical concepts directly to practical programming tasks, enhancing the ability to solve real-world problems.
  • Develop strong coding skills in C through hands-on exercises and assignments that reinforce mathematical principles.
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Odd Semester

Courses for this semester

Course Overview

An introduction to the design and analysis of computer communication networks. Topics include application layer protocols, Internet protocols, network interfaces, local and wide area networks, wireless networks, bridging and routing, and current topics.

Course Outcomes

  • Understand basic concepts, OSI reference model, services and role of each layer of OSI model and TCP/IP. Apply channel allocation, framing, error and flow control techniques.
  • Describe the functions of Network Layer. Explain the different Transport Layer function i.e. Port addressing, Connection Management, Error control and Flow control mechanism.
  • Explain the functions offered by session and presentation layer and their Implementation.
  • Discuss the different protocols used at application layer i.e. HTTP, SNMP, SMTP, FTP, TELNET and VPN.
  • Understand design issues in Network Security and to understand security threats, security services and mechanisms to counter.

Course Overview

This course offers detailed concepts, designing and implementation of different software development models. It includes Project management concepts, Risk management concepts, Quality Assurance, Software testing and debugging strategies.

Course Outcomes

  • Understand software engineering principles involved in building large software programs and process of requirements specification and requirements validation.
  • Understand the concepts of object orientation and development of class models.
  • To sensitize the students to the fundamentals of User Centered Design and User Experience their relevance and contribution to businesses
  • Analyze system models for designing patterns.
  • Apply estimation techniques, schedule project activities and compute pricing.

Course Overview

A computer programming paradigm called object-oriented paradigm, or OOP, arranges the design of software around data, or objects, as opposed to functions and logic. In this course Object-oriented Paradigm concepts including inheritance, association, aggregation, composition, polymorphism, abstract classes, and interfaces are taught along with how to design and construct programs using them.

Course Outcomes

  • Understanding fundamental principles of OO programming, OO analysis, design and development.
  • Apply inheritance and polymorphism concepts of OOPs on computing problem.
  • Design applications for a range of problems using file and exception handling.
  • Implementation of object oriented based projects.
  • Demonstrate the use of various OOPs concepts with the help of programs

Course Overview

This course will provide an introduction to the principles and techniques of exploratory data analysis. Students will learn how to use visual and quantitative methods to explore datasets, identify patterns and relationships, and detect anomalies. The course will cover topics such as data cleaning and preparation, graphical methods for data exploration, summary statistics and descriptive analysis, and basic statistical inference. Students will also learn how to communicate their findings effectively through data visualization and reporting. By the end of the course, students will have a solid understanding of the EDA process and be able to apply these techniques to real-world datasets.

Course Outcomes

  • Understand key statistical methods and programming syntax crucial for EDA.
  • Analyze statistical measures and comprehend the role of data visualization in effective communication.
  • Apply statistical methods and programming skills to analyze and manipulate datasets in EDA.
  • Evaluate data visualizations for patterns and outliers, and assess the relevance of statistical methods in specific contexts.
  • Develop strategies for data visualization and integrate statistical analysis with programming for comprehensive data-driven solutions.

Course Overview

This course delivers a comprehensive introduction to the principles and real-world applications of artificial intelligence (AI) and machine learning (ML). The students will gain hands-on experience with data preprocessing, feature engineering, and model building using industry-standard tools. The course covers different ML algorithms and their implementation. Additionally, the students will delve into the ethical considerations of AI, learning about bias, fairness, and transparency to help you implement AI solutions responsibly. By the end of this course, students will have the skills to develop effective AI and ML models that address real-world problems while considering their broader societal impact.

Course Outcomes

  • Gain a comprehensive grasp of foundational AI and machine learning concepts, encompassing algorithms and methodologies.
  • Develop proficient hands-on skills in implementing AI and machine learning models, utilizing industry-relevant programming languages and frameworks
  • Acquire expertise in preprocessing and analyzing data, mastering techniques for feature selection and engineering to enhance model performance
  • Demonstrate a sound understanding of model evaluation principles and optimization techniques, ensuring the ability to enhance model efficiency and effectiveness
  • Explore the ethical dimensions of AI, examining issues related to bias, fairness, and transparency, and develop strategies for addressing societal implications responsibly.

Course Overview

This course provides students with a comprehensive understanding of predictive analytics and data mining techniques. Students will learn to critically apply concepts and methods to extract meaningful insights from data, solve real-world problems, and improve decision-making processes.

Course Outcomes

  • Gain a comprehensive understanding of predictive analytics and data mining techniques
  • Develop skills to critically apply various concepts and methods to extract meaningful insights from large datasets
  • Learn to solve real-world problems using data-driven approaches
  • Enhance decision-making processes through the application of predictive analytics
  • Cultivate the ability to effectively communicate analytical findings and insights to a variety of audiences

Course Overview

This course provides students with a comprehensive understanding of predictive analytics and data mining techniques. Students will learn to critically apply concepts and methods to extract meaningful insights from data, solve real-world problems, and improve decision-making processes.

Course Outcomes

  • Develop a comprehensive understanding of predictive analytics and data mining techniques.
  • Learn to critically apply various analytical concepts and methods to extract insights from data.
  • Apply data-driven solutions to address and solve real-world problems.
  • Enhance decision-making capabilities using insights derived from data analytics.
  • Improve skills in interpreting and communicating analytical results to support organizational strategies.
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Even Semester

Courses for this semester

Course Overview

This course delves into the fundamental concepts and techniques used to design and analyze algorithms, which are the step-by-step instructions that computers follow to solve problems. It provides a crucial basis for anyone desiring to work in the field of information technology and computer science.

Course Outcomes

  • Analyze worst-case running time based on asymptotic analysis and justify the correctness of algorithm for a given problem.
  • Describe the greedy paradigm, dynamic-programming paradigm and divide-and-conquer paradigm.
  • Design a given model engineering problem using graph and write the corresponding algorithm to solve the problems.
  • Understand NP completeness and identify different NP complete problems.
  • Discuss various advanced topics on algorithms.

Course Overview

This course covers the data mining process, techniques, and tools, empowering students to solve real-world problems. They'll learn to design mathematical models for decision-making using business intelligence and apply Natural Language Processing for data analysis.

Course Outcomes

  • Develop an understanding of the data mining process and issues.
  • Understand various techniques for data mining
  • Apply the techniques in solving data mining problems using data mining tools and systems
  • Design mathematical model for decision making using business intelligence
  • Analyse and apply Natural Language Processing

Course Overview

This course provides a comprehensive overview of AI for students equipped with fundamental knowledge in areas like machine learning and deep learning. It offers practical applications in deep learning, natural language processing (NLP), and computer vision, leveraging industry-leading tools such as IBM Watson services. Through hands-on experience, participants develop proficiency in implementing AI techniques to solve real-world problems effectively. Emphasizing critical thinking, the curriculum navigates ethical considerations inherent in AI technology, fostering responsible innovation. This holistic approach equips students to navigate and excel in today's rapidly evolving AI landscape while ensuring ethical integrity and societal impact.

Course Outcomes

  • Demonstrate understanding of advanced AI concepts, including machine learning and deep learning, by applying them in real-world scenarios.
  • Utilize industry-standard tools like IBM Watson to implement practical solutions in natural language processing and computer vision.
  • Develop hands-on expertise in designing and deploying AI models that address specific problems across various domains.
  • Critically evaluate the ethical implications of AI technologies and incorporate responsible practices into AI solutions.
  • Prepare for advanced studies or careers in AI by mastering the skills necessary to innovate and lead in a technology-driven environment.
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Scholarship

Apply Scholarship through CST

CST- Common scholarship test is a national and international level online MCQ based examination funded for intellectual empowerment by Assam down town University.

CST- Maximum enrolment each year is 120 seats and any 10+2 students can apply. Adtu is northeast India’s first placement driven university to provide 100% scholarship benefits worth 10 cr.

CST aims to inspire brilliant and competent students to pursue further education. Accredited with a prestigious grade by NAAC, UGC and AICTE.

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National & International Level 100% Scholarship on all semester
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District Level & NCC Certificate Holder 25% Scholarship on all semester

A 50% scholarship on total semester fees is provided to all specially abled students.

A 100% scholarship on the last semester fee is provided to all the alumni of Assam down town University.

A 100% scholarship on total semester fee for Economically Backward Classes

Campus Life

Our Facilities

World Class Facilities

Discover a multitude of world-class amenities and cutting-edge resources at Assam down town University, enhancing your academic journey to new heights.

Some of our Facilities
  • Library
  • Swimming Pool
  • Play Ground
  • Amphitheatre
  • Basketball Court
  • Cinema Hall
  • Cafeteria
  • Canteen
  • Indoor stadium
  • Yoga Studio
  • Gym
  • ATM

Start-Up &
Incubation Centre

The Start-Up & Incubation Centre at Assam down town University provides a supportive environment for young entrepreneurs to develop and grow their business ideas. The center provides mentorship, funding, and networking opportunities to help innovative ideas become successful businesses.

Rural Empowerment with SFURTI scheme

SFURTI scheme to support rural entrepreneurs and innovators, an initiative by the Ministry of MSME

TIDE 2.0 scheme for ICT-based startups

TIDE 2.0 scheme for ICT-based startups which provides a grant of Rs. 4L and Rs. 7L under EiR and Grant categories respectively, an initiative by the Ministry of MeitY.

dtVL Ideation interest-free loans up to Rs. 2 lakhs.

dtVL Ideation, an incubation program for early-stage entrepreneurs with a market-ready solution/product, offering interest-free loans up to Rs. 2 lakhs.

Innovation with Sprout UP program

Sprout UP, an incubation program for students, faculties, and researchers with innovative business ideas, prototypes, or technology solutions.

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Currently I am pursuing MBA in Assam Down Town University. MBA is the professional course through wh...

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AdtU is a university that focuses on giving knowledge, education and simultaneously making the stude...

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My experience with AdtU has been splendid one indeed. Little needs to said about its scenic infrastr...

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As a student I am very glad that I have got an opportunity to study here in Assam downtown universi...

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AdtU is a platform where I got golden opportunities to feed my zeal for knowledge through the dynami...

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I am fortunate to get an opportunity to study here in Assam Downtown University. The best thing abou...

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Our university is one of the best place for developing ourselves in the field of research and acedem...

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ADTU is a university that is very good interms of infrastructure, academics and placements. Our tea...

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