LEARNXT

SRM University AP Advantage

Accredited Degree from India's Leading University

Latest Applied Data Science Curriculum

High Quality Faculty with IIT and Global University Pedigree

High Impact Career Services and Placement assistance through CareerNxt Platform

Career Mentorships with Industry Experts

Hybrid Learning, Campus Immersion, Internship, Lifetime Access to Courseware on our AI based StudyNxt Platform

Industry Relevant Case Studies, Assessments, Assignments and Capstone Projects

Learning materials and Simulations from Harvard Business Publishing

Alumni Status of SRM University AP

Online and Offline Networking Events

About Programme

The two-year MSc (Applied Data Science) offered in both full-time classroom and weekend hybrid program is intended for working professionals who want to pursue a career in data science and machine learning. The programme will give you a platform to develop and practice the skills in concepts such as statistics, computer programming, machine learning and artificial intelligence

The primary focus of the programme is to equip you with principle concepts of data science and application of the same in real-time business scenario. The case studies, presentations, assignments, and assessments will give you hands-on experience and insights into the practical and theoretical aspects of data science.

The internship in the programme will help you gain valuable work experience, explore a career path, give you an edge in the job market, develop network with professionals in the field, and allow you to test specific techniques learned in the classroom before entering the working world.

The interaction with industry experts will provide you knowledge of the current trends and skills required for employment.

About SRM University AP

EXPERIENCE THE ART AND SCIENCE OF LEARNING WITH SEAS AND SLABS AT SRM University AP

Spread over 200 acres, SRM University AP is a place where different streams converge. And talent across disciplines; engineering to medicine, liberal arts to management, comes together. The Multi-stream research university has the vision to become a truly global world-class institution in the next 10 years with 20,000+ students and 1,500 faculty members.

A Coveted Destination for Higher Education

At SRM University AP, we believe that our future should be in the hands of the best and the brightest. And they should have access to all the resources and advantages of a new-age education destination.

Infrastructure

Designed by Perkins + Will, the campus has learning spaces both in and outside classrooms, clubs, recreational facilities, accommodation and dining facility

Hand-Picked Faculty

SRM University AP picks the best and the most dedicated faculty from across the globe

Curriculum

SRM University AP offers a flexible curriculum with IDEAL (Inter Disciplinary Experiential Active Learning). This is at par with curriculums offered by MIT and Stanford. With IDEAL, students can puruse Minors and Specializations along with their Major, and research and design opportunities including internships, the Capstone project and more.

Collaborations

SRM University AP has signed several MoUs, including one with UC Berkeley College of Engineering for Entrepreneurship and Semester Abroad programs and MITx, US for licensing MITx courses.

Research Outlook

The University's award-winning Next Tech Lab is a platform to learn, research, and implement big ideas that lead to the creation of organizations and products that make a difference.

Global Academic Collaborations

Global Collaborations to create a Silicon Valley at Amaravati

MIT Curriculum and hybrid learning leveraging MIT

Opportunity for students to intern / do projects in Premier International Universities

Programme Highlights

Earn a MSc (Applied Data Science) post-graduate degree from SRM University AP
Learn from faculty with IIT and global University pedigree. Mentored by industry experts
Learn advanced Applied Data Science concepts such as, Enterprise Machine learning, Data Lakes, Machine learning pipelines, advanced data visualization best practices and storytelling concepts, managing Machine learning models, Artificial Intelligence domains including Natural language processing, Image, voice and video processing
Gain the coveted alumni status of SRM University AP. Get introduced to alumni network of SRM Group. Network with peer data scientists through private online and offline events
Experiential learning through concepts and real-life case-studies, simulations from Harvard Business Publishing
A unique and comprehensive learning approach to develop skills and competencies in machine learning, deep learning and artificial intelligence
Capstone project – Work on a full-fledged Industry project in data science to sharpen the skills
3 months internship – Get a real-time data science experience through the network of our corporate partners
Lifetime access to the courseware on AI based StudyNxt Platform
Access high Impact Career Services and Placement assistance through CareerNxt Platform.

Module
Presentations

Hands-on
demonstrations

Access to AI Lab

90 Assignments

26 Case studies

15 Assessments

Capstone project

1800+ hours of
learning

15 days campus
immersion

Tools Covered in the Program

Faculty

Dr. Jatindra Kumar Dash

PhD (Machine Learning and Image
Retrieval), IIT Kharagpur
Visiting Researcher in the
Department of SCET,
University of California,
Berkeley, USA

Dr. Murali Krishna Enduri

PhD Computer Science and Engineering,
IIT Gandhinagar Worked as Post Doctoral
Fellow in Department of Computer Science
and Engineering at IIT Madras.

Dr. T. Ragunathan

PhD (Computer Science & Engineering),
IIIT-Hyderabad Worked at IIT Hydrabad
and IIIT-DM, Kurnool as Teaching Faculty

Dr. A Vadivel

PhD (Computer Science and Engineering),
IIT Kharagpur TA / Faculty at
IIT Kanpur and NIT Trichy

Dr. Sandeep Singh Sengar

PhD (Computer Science and Engineering),
IIT-Dhanbad M.Tech (Computer Science and Engineering),
NIT-Allahabad

Programme Curriculum

Semester I

Statistical Foundations

Introduction to Statistics & Probability
Sampling and Testing Hypothesis
Non-Parametric Methods, Correlation and Regression
Discrete Probability Distributions
Continuous Probability Distributions

Mathematics for Data Science

Linear Systems and Vector spaces
Linear Transformation
Metrics and Its Properties
Multivariable Calculus
Vector Analysis

Data Analysis Fundamentals

Introduction to Data Science
Python programming foundations
Pandas for data Analysis
NumPy Basics and Manipulation
Statistical foundation for Data Science

Data Visualization & Concepts

Introduction to Tableau
Data Visualization Concepts
Data Dashboards using Tablet
Open Source Data Visualization with Seaborn
Open Source Data Visualization with Matplotlib, Bokeh And Pygal

Data Engineering and Governance

Data Architecture
Big Data
Data Lake Architecture
Data Lake on Aws
Distributed Computing using Spark

Data Analysis Fundamentals – Lab

Implement function overloading with different function signatures.
Implement concept of class, instances and inheritance
Solve algorithmic problems by program using different problem-solving strategies
Search content using regular expression library in Python
Perform Linux administration task using Python

Data Visualization & Concepts - Lab

Bubble Charts, Radar Charts, Polar Charts, Range Chart
Box-And-Whisker Plots, Univariate Scatter Plots, Histograms Word Cloud
Multi-Dimensional Data Visualization; Manifold Visualization; Graph Data Visualization

Semester II

Data Structures and Algorithms

Data Architecture
Sorting and Searching
Trees & Graphs
Algorithmic Paradigms
Hard and NP- Complete Problems

Building Machine Learning Pipelines

Data Governance
Linear Algebra Basics for Data Science
Matrices and Operations
Data Transformation Methods
Feature Engineering Methods

Machine Learning for Data Science

Introduction to Machine Learning
Introduction to supervised Learning algorithms –LDA & SVM
Stochastic Gradient Descent, Naive Bayes, Decision Trees, Ensemble methods
Multiclass and multilabel algorithms & Feature selection
Unsupervised Learning Algorithms

Machine Learning Model Management

ML Model Evaluation and Selection
ML Model Management
Hyperparameter tuning, versioning and Deployment
Recommendation Algorithms
Recommendation Evaluation and Validation

Building Machine Learning Pipelines - Lab

Collecting and Manipulating data, describing Similarity neighbourhoods, creating a Recommendation Engine,
Recommending Another Item, Finding Items to Recommend, Recommending Items Based on Other Items
Evaluating a Recommendation System, Validating a Recommendation System

Machine Learning for Data Science - Lab

Assuming a set of documents that need to be classified, use the naïve Bayesian
Classifier model to perform this task. Built-in Python classes/API can be used to write the program. Calculate the accuracy, precision, and recall for your data set.

Mid-term Project

Real life business case to be allocated to each student. Students can also opt for “bring your own project model” (BYOP)

Semester III

Cloud Computing

Cloud Computing Fundamentals
Cloud Applications
Management of Cloud Services
Application Development
Cloud IT Model

Deep Learning for Data Science

Introduction to Neural Network
Fine Tuning Neural Network Models
Introduction to Deep Learning with Keras
Advanced Deep Learning Models

Enterprise Machine Learning

Machine Learning in Enterprise & Data Compliance Strategy
ML in Enterprise – AWS
ML in Enterprise – Azure
ML in Enterprise – GCP
Refactoring And Best Practices of ML Model

Artificial Intelligence

Introduction to AI
Convolutional Neural Network for Image Processing
Recurrent Neural Network for Sequence Modelling
Natural Language Processing and Deep Learning
Reinforcement Learning

Deep Learning for Data Science - Lab

Train A Simple Deep Network
Effectively Regularise a Simple Deep Network
Train a competitive Deep Network via Model Exploration and Hyper- Parameter Tuning.
Setting up ANN setting up DNN setting up CNN setting up RNN

Enterprise Machine Learning - Lab

Introduction to NLP and Deep learning word vector representations: Word2Vec
Word window classification and Neural networks image classification with Deep convolutional networks sequence labelling with Deep recurrent networks
Feedforward Networks for handwritten digit recognition

Internship

3 months internship – Get a real-time data science experience through the network of our corporate partners

Semester IV

Capstone Project

A full-fledged industry project submission to SRM University, AP towards partial fulfilment of the criteria for degree award of MSc (Applied Data Science) by SRM University, AP

Mini Projects

Project 1: Deep Learning Model for Stress Detection

There are a plenty of wearable devices such as Apple watch, Fitbit Watch and other wearable technologies. Those wearable devices monitor our health, activities, health conditions, use that information to provide customized recommendations for us to follow good and healthy habits and at the same time stopping or reducing the unhealthy and bad habits. Stress is one of the silent killer in this century, as long as we can monitor and detect stress and it’s behavior and patterns, we can find out solutions and medications to handle it. In this case study the objective is to understand the dataset provided and organize the data in such a way to represent the information to anyone. Apply the deep learning models to predict stress and classify the results.

Project 2: Deploy ML Model for Fraudulent Transactions Identification in credit card spends

In the following dataset there are 492 fraudulent transactions, which is 0.172% of the total transactions. Try to identify those 492 transactions using the outlier detection methods and report out the accuracy, that is how many fraudulent transactions your outlier detection technique can successfully detect out of total 492. The objective is to deploy the trained model, hence generate the model trained in the form of PMML script, Pickle Dump and Joblib dump. Using the above format you should be able to upload any dataset and generate predictions for any new transaction.

Project 3: Advertisement Recommendation from internet traffic

This use cases involves recommendation of advertisement on internet pages, whether a page has advertisement present or not. If no advertisement is present, can we potentially identify those pages and recommend to relevant advertisers given the fact that they have many visitors to their website. It is important to generate the recommendations when the customer is active and live on the web page and the recommendation generation process should not take much time and the length of stay on a particular web page is very less. Build the entire recommendation model using different algorithms and verify the best algorithm that fits to the scenario.

Project 4: Calorie Prediction using Neural Network Model

Epicurious - Recipes with Rating and Nutrition is a dataset available over Kaggle, Recipes from Epicurious by rating, nutritional content, and categories have been provided. The objective here is to analyze the data, work on feature engineering and predict the calories based on the content of the recipe, for example given a list of ingredients your model should be able to predict how much calorie it contains, this is especially of importance to the nutritionists. For the restaurant owners it is also important to understand the user's choice and preference towards any particular recipe. Hence create another model predicting the rating that customers would like to provide based on the content of the recipe (title).

Project 5: Neural Network for Classification Model

In the case study the insurance company has given Information about customers consists of 86 variables and includes product usage data and socio-demographic data derived from zip area codes. The data was supplied by the Dutch data mining company Sentient Machine Research and is based on a real world business problem. The training set contains over 5000 descriptions of customers, including the information of whether or not they have a caravan insurance policy. A test set contains 4000 customers of whom only the organizers know if they have a caravan insurance policy.

Why SRM University AP MSc (Applied Data Science) ?

Strong Data Science Skills Career Outcome Learning Convenience for
Working professionals Financing support

The only university in the country offering accredited Postgraduate Degree in MSc (Applied Data Science) with latest Applied Data Science curriculum

Learn advanced Applied Data Science concepts such as, Enterprise Machine learning, Data Lakes, Machine learning pipelines, advanced data visualization best practices and storytelling concepts, managing Machine learning models, Artificial Intelligence domains including Natural language processing, Image, voice and video processing

Faculties with IIT and Global University Pedigree

Gain SRM University AP alumni status and get opportunity to interact with peers from across globe

Access to career services such as, Resume building, Mock interviews, Career planning, Skilling programmes & industry connect for job through CareerNxt platform

One-to-one regular guidance & personalized feedback from industry mentors on personal improvement

3 months internship opportunity with our corporate partner to work on the real time data science projects

Access to online and offline events and network with SRM University AP alumni, peer data scientist and industry mentors

The 2 year's weekend hybrid degree program including 15 day's campus immersion is designed to suite working professionals and full-time classroom program for fresh graduates

Total 1800+ hours of learning with 70% practical & projects

Life time access to courseware on Ai based LMS gives opportunity to revisit study materials & video lectures to refresh the Applied Data Science skills

The curriculum is aligned as per the industry requirement which emphasizes on case studies, assignments, assessments, and capstone projects

Easy financing options for admissions

Loans can be availed from the leading banks

Our unique scientific approach to career management services will help you to introspect the right opportunities as per your specialisation. It gives you the right direction to define your career goals and develop a step by step plan and access relevant services offered to achieve the goal. As part of the career building process, we offer the below services:

Career Planning

CareerNxt platform will help you to prepare for the placement season. You will have access to industry expert guidance on latest hiring trends, skills analysis and get the recommendations to build a career plan, which is relevant and focuses on the right career path. The self-analysis activity will provide a quick assessment to know your skills, strengths, and work towards developing a sense of career ownership and accountability to land your dream job.

Resume Building

The resume building will have personalised guidance from industry experts to build the resume and cover letter, which will highlight projects, certifications, industry sponsored internships and other achievements. It provides an opportunity to create a 30 second video resume to showcase your personal branding and personality.

Mock Interview

iView is an innovation career development solution that combines revolutionary web-based technology with career advice and on-line resources to help you assess and develop critical communication and presentation skills. The solution includes personalized mock interview with specialised career coach to provide feedback on both functional & behavioural skills, which will help you assess the readiness for the job interviews with the targeted organisation and job role.

Career Coaching Services

The personalized career coaching services will enable students to identify their strengths and interest areas to choose an appropriate career. The service will benefit all the learners to choose possible career paths through mapping of self-assessment results. It includes career assessment review, evaluation of career options, creation of self-marketing plan, personal branding, interviews and negotiation skills.

Internship

The academic/ industry projects will be mentored by the industry experts from relevant vertical. You will be provided 2-3 month's company sponsored internships to work on real time assignments, which can be in person or virtual as per the industry policies.

Job Search Support

Active job opportunities will be shared on regular basis as per your skill matrix. The job description will help you get an insight on the roles and responsibilities, along with other information. The interview process will be briefed during the pre-placement session.

Certificate

Students will be awarded MSc (Applied Data Science) post-graduate degree certificate by SRM University AP post completing the programme and meeting all the certification requirements of the University.

Admissions

SRM University AP uses a rigorous set of admission criteria including a combination of academic scores, assessment of interpersonal skills and fitment to a career in data science and machine learning sector.

Check eligibility

IT / BSc Computer Science/ BCA/ BSc Mathematics / BSc Statistics/ BSc Physics/ BSc Electronics / Triple major subjects with Computer Science as one of the Major subjects
Minimum of 50% in 10th, 12th and graduation
Minimum 2 years of work experience is preferred for part-time and fresher may apply for full time classroom program

Apply Now

SRM Group Universities and Institutes

SRM Group Accreditations

About

LEARNXT is an SRM Group initiative with a vision to creating a global digital learning company, empowering people to achieve their dreams through education.

LEARNXT provides learning products, solutions and services by leveraging high quality intellect hand-picked across the globe. The rigorous curriculum and content are created and curated with deep understanding of industry and individual learning needs. The most innovative learning and teaching experiences are orchestrated over state of the art brick and click infrastructure with a strong intent to measure and report learning outcomes.

FAQs

Programme Related

1. Will this program be treated at par with regular MSc programme?

All students would get a MSc (Applied Data Science) degree from SRM University, AP under UGC guidelines. There will not be any discrimination w.r.t full-time degrees. It carries the same credentials as any post-graduate degree.

2. Can the programme be opted from any location?

Yes, this is a two-year weekend hybrid program designed for both working professionals. Therefore, candidates from any location can opt for this programme. However, the programme has 5 days’ campus immersion (5 days per semester) which is mandatory for all students. Any exception shall be reviewed by the management

3. How semester exams are scheduled? will there be any slots to choose or any specific dates?

All the exams would be scheduled on a specified time and date which would be announced well in advance.

4. What will be the mode of appearing the semester exams?

All the final semester exams would be conducted at the campus. All the unit level exams (2 per semester) would be conducted through online platform on a specified time and date.

5. If candidate doesn’t attend mandatory classes due to any unforeseen events/ work commitments, what will be the scenario?

The schedule would be rolled out prior to the beginning of the semester. The campus immersion is mandatory for peer-to-peer learning. Considering the uncertainty due to pandemic, few exceptions are allowed basis the approval from the academic team

6. Will candidates be informed in prior for campus immersion dates since there are working professionals as well and will it be ok to skip in case of uncertain condition or is it mandatory?

Yes, the schedule would be rolled out prior to the beginning of the semester. The campus immersion is mandatory for peer-to-peer learning. Considering the uncertainty due to pandemic, few exceptions are allowed basis the approval from the academic team.

7. Will the 4th semester be only Capstone or will it have subjects to study as well?

It would be only for the capstone project and few mentoring live sessions for project work. No core paper or elective would be covered during 4th semester.

8. Is the curriculum and syllabus updated as per the current industry standard?

Yes, the curriculum of the programme is focused on the latest skillset required for Data Science and Machine Learning industry standards. As part of the programme, you will learn advanced Applied Data Science concepts such as, Enterprise Machine learning, Data Lakes, Machine learning pipelines, advanced data visualization best practices and storytelling concepts, managing Machine learning models, Artificial Intelligence domains including Natural language processing, Image, voice and video processing.

9. What are the tools covered as part of the programme?

As part of the programme, the candidates will hands-on with Python, Tableau, Pandas, Numpy, Seaborn, Matplotlib, AWS-Data lakes, SQlite, Spark, NLTK,Scikit learn, Joblib, Pickle(HDF5) and many more tools.

Eligibility and Admissions

1. What is the eligibility criteria for MSc ( Applied Data Science) programme?

Candidates fulfilling the below criteria can apply for this programme:

BSc IT / BSc Computer Science/ BCA/ BSc Mathematics / BSc Statistics/ BSc Physics/ BSc Electronics / Triple major subjects with Computer Science as one of the Major subjects with a minimum of 50% in 10th, 12th and graduation
Graduates working in the Data Science industry and IT professionals
2 years of work experience is preferred

2. Can distance education candidate join the program?

Yes, we accept admissions from distance learning programs in the specified disciplines.

3. How many attempt will I get to clear the entrance test?

The candidates will get only one chance per admission cycle to attempt the admission test.

4. Can the final year degree students apply for this programme?

No, Minimum of 2-year experience is preferred for the programs. Few exceptional profile shall be considered basis the approval for the academics team.

5. What are the document required for admission?

Photograph, 10^th and 12^th marks sheet, Aadhaar Card, PAN Card, Bona fide Certificate, Caste Certificate, Migration Certificate, Graduation Certificate or Provisional Certificate for Students in Final Year of Graduation.

Fees Related

1. Will the fee of the program include Semester fee?

Yes, INR 1.6L includes the entire fee of the program. Only campus travel and accommodation would be borne by the candidate. The accommodation charges would be INR 2000 per day which sums to INR 10,000 for 5 days in each semester. Students are free to choose their own accommodation.

2. Is there any EMI option available for paying the programme fee ?

Registration fee of INR 10,000 is one-shot. Students can also opt for our loan from our financial partners. The 1st year fee can be paid through loan with different EMI options. If not opting for loan, the entire 1st year should be paid one-shot within 10 days of receival of PAL.

3. Is there any refund if admission is cancelled?

Refunds are processed as per university norms. Candidates are requested to click here for more details: https://srmist.edu.in/admission-india/admission-fee-refund-policy-school-of-management/

4. Is there any financing support offered to pay the programme fee?

Yes, there are easy financing option available for the candidates through our financing partners.

Placements and Career Services

1. Is there any placement guarantee provided for this programme?

Candidates will be given job support services along with all required services to prepare for the job interviews. All candidates would get access to CareerNxt platform which is a 360° career support tool. It includes resume writing section, company shortlisting, industry talks, mentor sessions, alumni meets, job interview support and evaluating a job offer.

2. What are the career services support will be provided?

The candidates will be given CareerNxt tool to access various services such as career planning, resume building, mock interviews, networking with industry expert & career coach and job search. For more details on our career services, request to visit the programme page or talk to our advisor

3. What is the eligibility criteria for appearing for placement?

The successful completion of each semester.

Programs

MSc (Applied Data Science)

UGC Approved Degree

SRM University AP Advantage

About Programme

About SRM University AP

EXPERIENCE THE ART AND SCIENCE OF LEARNING WITH SEAS AND SLABS AT SRM University AP

Global Academic Collaborations

Programme Highlights

Tools Covered in the Program

Faculty

Dr. Jatindra Kumar Dash

Dr. Murali Krishna Enduri

Dr. T. Ragunathan

Dr. A Vadivel

Dr. Sandeep Singh Sengar

Programme Curriculum

Why SRM University AP MSc (Applied Data Science) ?

Career Planning

Resume Building

Mock Interview

Career Coaching Services

Internship

Job Search Support

Certificate

Admissions

Check eligibility

SRM Group Universities and Institutes

SRM Group Accreditations

About

FAQs

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