Machine Learning &Big Data Analytics

PG Certificate Program in

FROM CSTCPIIIT ALLAHABAD, PRAYAGRAJ

BATCH-2

Certificate of Completion and Alumni Status of CSTCP-IIITA

Overview

Program Highlights

Organizations today operate in a world surrounded by data and data that is understood and analyzed smartly can

play a pivotal role in determining the success of many businesses. Data Science, through its various inherent tools

and techniques, is successfully adding value to all the business models by using statistics and deep learning to

make better, relevant and timely decisions. Understanding the dynamics of data and knowing how to deal with data

has therefore become a critical skill in an organizational context. No wonder that Harvard Business Review has

termed Data Scientist as the Sexiest Job of the 21st Century!

The objective of this course is to introduce participants to the intricacies of data science and techniques of

machine learning. This course will expose participants to hands-on experience of popular and in-demand tools in

the BDA and ML area and has been designed with an intention to impart practical problem solving skills to

participants which in turn will enhance prospects of career growth in this sunrise domain.

On successful completion of the course, earn a Certificate of Completion and gain Alumni Status of

CSTCP-IIITA

Learn from the Eminent Faculty of IIIT AllahabadLectures imparted by eminent faculty from IIIT Allahabad and Subject Matter Experts

6 Days of On-Campus Immersion Modules at IIITA, PrayagrajTwo Campus Immersion modules of 3 days each, at the commencement and culmination of the program, thatprovides participants with an opportunity to experience the campus, meet the faculty and network with peers

Practical Approach towards Learning Course completely oriented towards imparting practical and application oriented knowledge throughwalkthroughs, demonstrations and class exercises to develop hands-on skills

Hands-on Practical ExposureProgramming languages and tools covered include Python, Scikit Learn, Tensor Flow etc.

1 Month Integrated InternshipOpportunity to complete 1 month of professional Internship doing hands-on projects with TransOrg Analytics

Career Coaching & Job Search Support3 Months Long Individual Career Coaching and Job Search Support

Capstone ProjectA highly extensive project requiring the participants to apply all of their learning to practical use

EligibilityFor Indian Participants - Graduates (10+2+3) or Diploma Holders (only 10+2+3) from a recognized university

(UGC/AICTE/DEC/AIU/State Government) in any discipline

For International Participants - Graduation or equivalent degree from any recognized University or Institution in

their respective country

Program Prerequisites

Mathematics or Statistics as a subject in Class XII or Graduation

Formal education in or knowledge/experience of at least one programming language

This program is entirely hands-on and so it is recommended, though not a necessity that students have two

devices (laptop/desktop) – one to follow the lecture, and the other for hands-on practice alongside during

the class

Who Should Attend

IT PROFESSIONALS FROM VARIOUS DOMAINS - Developers, Software Engineers and Database Architects

aspiring to gain expertise in the field of Data Science or Machine Learning

ANALYSTS - Business and Data Analysts who are responsible to churn through and infer from large databases

and handle big data based projects

TECHNOLOGY ENTHUSIASTS - Professionals seeking to gain a deeper understanding of ML algorithms

WORKING PROFESSIONALS - Executives looking to embark on a career in Machine Learning

Certificate

Participants, who successfully complete the evaluations and satisfy the requisite attendance criteria, will be awarded a certificate of completion.

Participants who are unable to clear the evaluation criteria but have the requisite attendance will be awarded a participation certificate.

1. FUNDAMENTALS OF PYTHON (By Industry Partner)

• Introduction to Python: A brief introduction to Python and its installation along with different Integrated Development Environments (IDE) that support Python

• Python basics: Understanding different variable types and ope operators in Python

• Python data structures: Working with different data structures and their usage such as list, dictionary, and Tuple

• Python programming: Understanding concepts of control and looping, conditional statements, and functions in Python programming

• Use of standard libraries: Working with Python packages which are specifically tailored for certain functions, such as:

• NumPy: Also known as Numerical Python mostly used in mathematical operations • Pandas: Package to build data frames used for creating features and processing the data • Matplotlib and Seaborn: Packages used for data visualization in Python• • Statsmodel and Scipy: Used for statistical modelling and testing• Scikit-Learn: Used for machine learning and advance analytics algorithms

Data scientists must know how to code - start by learning the fundamentals of one of the most popular programming languages - Python.

2. DATA WRANGLING

• Reading CSV, JSON, XML and HTML files using Python• NumPy & Pandas

Once you have the core skill of programming covered– dip your feet in the nitty - gritties of working with data by learning how to wrangle and visualize them.

3. MATHEMATICAL FOUNDATION FOR DATA ANALYSIS

• Probability & Statistics• Descriptive Statistics & Data Distributions• Probability Concepts and Set Theory• Probability Mass Functions• Probability Distribution Functions• Cumulative Distribution Functions• Modeling Distributions• • Inferential Statistics• Estimation• Hypothesis Testing• Implementation of Statistical Concepts in Python

• Vectors• Eigen Vectors & Eigen Values• Matrix Manipulation• Rank

• Linear Algebra

• Relational Databases and Data Manipulation with SQL• Scipy Libraries• Loading, Cleaning, Transforming, Merging, and Reshaping Data

It is impossible to use data without knowledge of mathematics. Collect, organize, analyze, interpret, and present data using these concepts of mathematics specially probability, statistics and linear algebra.

Syllabus

4.MACHINE LEARNING MODELS IN PYTHON

Machines have increased the ability to interpret large volumes of complex data. Combine aspects of computer science with statistics to formulate algorithms that help machines draw insights from structured and unstructured data.

• Building Models Using Below Algorithms• Linear and Logistics Regression• Support Vector Machines (SVMs)

5. DATA VISUALIZATION USING MATPLOTLIB

Complex data sets call for simple representations that are easy to follow. Visualize and communicate key insights derived from data effectively by using tools like Matplotlib.

• Interactive Visualizations with Matplotlib• Dashboard Development• Exploratory Visualization

6. DEEP LEARNING USING TENSORFLOW

Go beyond superficial analysis of data by learning how to interpret them deeply. Use deep-learning nets to uncover hidden structures in even unlabeled and unstructured data using TensorFlow.

• Basics of Neural Network• Linear Algebra• Implementation of Neural Network in Vanilla• Basics of TensorFlow• Convolutional Neural Networks (CNNs)• Recurrent Neural Networks (RNNs)• Generative Models• Semi-supervised Learning using GAN• Seq-to-seq Model• Encoder and Decoder

7. HANDLING BIG DATA WITH SPARK

Lastly, manage your infrastructure with a data engineering platform like Spark so that your efforts can be focused on solving data problems rather than problems of machines.

• Revision of Data Mining algorithms• Introduction to Big Data analytics & Spark• RDD's in Spark, Data Frames & Spark SQL• Spark Streaming, MLib & GraphX• Time Series Forecasting• Predictive analytics

• Random Forests• XGBoost• Decision Tree, Random Forest, K-Nearest Neighbors• Partition Based & Hierarchical Clustering• Principal Component Analysis• Text Analytics

• Focus on real business use cases• Enhance theoretical understanding with practical work• Learn directly from practicing Data Scientists and subject matter experts (SMEs)• Understand the applicability of AI and ML in a pa particular industry domain

This program includes two on-campus components of 3 days each which will take place at IIIT Allahabad campus. On Campus session 1 is tentatively scheduled towards end of July 2021 and On Campus Session 2 is tentatively scheduled towards end of May 2022. The final confirmed dates for On Campus sessions will be communicated in due course and sessions will be communicated in due course and is subject to Government advisory regarding Covid 19 situation. However, attendance to On Campus Component, when held, will be mandatory for all participants of this course.

On Campus Component

CAPSTONE PROJECT

ONE MONTH INTERNSHIP WITH TRANSORG ANALYTICS (INDUSTRY PARTNER)

Faculty

Dr. Manish KumarProgramme Co-ordinator

Dr. Manish Kumar has completed M.Tech (CS) from BIT Mesra and got Ph.D. degree from Indian institute of information Technology, Allahabad, Prayagraj, India on topic” Data Management in Wireless Sensor Networks. Presently he is working as an Associate Professor in Department of IT, IIIT-Allahabad. He is coordinator of research lab Data Analytics Laboratory (DAL) at IIIT-A. His His research interest includes Data aggregation, data processing, inference, Compressive sensing in WSNs & big data analytics.

Prof. Shekhar Verma Professor

Prof. Shekhar Verma received the Ph.D. degree in computer networks from the Indian Institute of Technology (BHU), Varanasi, India, in 1993. He is currently working as a Professor (IT) with the Indian Institute of Information Technology, Allahabad, India. His research interest includes machine learning, computer networks, wireless sensor networks, wiwireless networks, information and networks security, vehicular technology, and cryptography.

Dr. Neetesh PurohitAssociate Professor

Dr. Neetesh Purohit is an Associate Professor at IIITA Prayagraj. His research and development work in the fields of wireless communications, ICT and DSP has significant involvement of the principles of statistics.

His current research interests includes Blockchain technology, Network and Information Security. His teaching interest includes Compiler Design, Computer Networks, Blockchain and Cryptocurrency and Database Security.

Prof. T. LahiriProfessor

Professor Tapobrata Lahiri has completed his Ph.D from the University of Kalyani, West Bengal. Presently he is working as a Professor in the Department of Applied Sciences, Indian Institute of Information Technology, Allahabad.HisHis areas of interest and research include Application of Numerical Analysis Techniques (Machine Learning, Artificial Intelligence, Optimization, Systems Modelling and Simulation, Fractal Dimensional Analysis) to improve Prediction and Automatic Expert/Diagnostic Models for Biomedical area using data/feature extracted from mainly Digital Image and Signal PrProcessing.

Prof. O. P VyasProfessor

Prof. O.P. Vyas has done M.Tech. in "Computer Science & Data Processing" from IIT Kharagpur and Ph.D. in "Congestion Control and QoS provisioning in ATM Networks" under joint collaboration with Technical University of Kaiserslautern (Germany) and IIT Kharagpur.HisHis current Research interest includes Linked Open Data Mining, Cyber Security and Service Oriented Network Architectures. He teaches Object Oriented Software Engineering, Business Informatics, Data Mining & Warehousing, and guided 16 Research Scholars for Ph.D.

Dr. SatakshiVisiting Faculty

Satakshi received her M.Sc. (1998) and M.Phil (1999) in Mathematics from University of Roorkee. In 2004, she received a Ph.D. in Applied Mathematics from IIT Roorkee and later joined Birla Institute of Technology and Sciences, where she worked as a faculty of Mathematics for two years. In 2017, she joined Sam Higginbottom University of Agriculture, Technology and Sciences, where she is currently workingworking as a faculty in the Department of Mathematics and Statistics. Her research interests include order reduction of linear systems, optimization, Evolutionary Algorithms, Machine Learning, Time Series etc.

Dr. K P SinghAssociate Professor

Dr. Krishna Pratap Singh is an Associate Professor at Department of Information Technology, Indian Institute of Information Technology Allahabad. Prior to this he worked as an Assistant Professor (2013-2018), and Lecture (2009-2012) at IIIT

He did PhD & Master from IIT Roorkee in 2009 & 2004 respectively. He is heading Machine Leaning & Optimization Lab at IIITA. His teaching & research interests are Machine learning, representation learning, Transfer Learning & Optimization.

Dr. Bhaskar BiswasVisiting Faculty

Dr. Bhaskar Biswas is an associate professor in the Department of Computer Sc. & Engineering, Indian Institute of Technology (BHU), Varanasi. He acts as a visiting faculty at IIIT, Allahabad and teaches C PROGRAMMING and DATA STRUCTURES. His main areas of interest are Data Mining, Web Mining, and Social Network Analysis.

Dr. Pavan ChakrabortyAssociate Professor

Professor. Dr. Pavan Chakraborty teaches as Head of IT department at IIIT, Allahabad. He has vast areas of interests that include, Human Gait Analysis, Human Prosthetics, Bio-metrics, Image Processing, Graphics and Visual Computing, Graphical Projections, Robotics & Instrumentation, Real Time Simulation, High Performance Computing (HPC), Artificial Life Simulation and Intelligence, HumanHuman Computer Interaction, Astronomy & Astrophysics, Large Astronomical Data Analysis, Cometary Jets Simulation, etc.

S. VenkatesanAssociate Professor

Dr. Venkatesan Subramanian is an Associate Professor in the Department of Information Technology, Indian Institute of Information Technology Allahabad. He received Ph.D. in 2010 from the Department of Computer Science and Engineering at Anna University, Chennai, India in the area of Mobile Agent Security. He has published more than 20 papers in reputed International Journals and Conferences.

Dr. Ashutosh MishraAssociate Professor

Dr. Ashutosh Mishra earned his Ph.D. in Electrical and Computer Engineering from Old Dominion University, Virginia, USA. Currently, he is working as an associate professor of Biomedical Engineering (Dept. of Applied Science) at Indian Institute of Information Technology, Allahabad.

His main areas of interest include Bioelectrics, Learning Machines, Distributed Computation and Biomedical Instrumentation and Signals.

Dr. Sonali AgarwalAssociate Professor

Prof. Dr. Sonali Agarwal is currently working as an Associate Professor in the Information Technology Department of the Indian Institute of Information Technology (IIIT), Allahabad, India.She earned her Ph. D. Degree at IIIT Allahabad and later joined as a member of faculty, where she has been imparting education to aspiring engineers since October 2009. HerHer main interests are in the areas of Stream Analytics, Big Data, Stream Data Mining, Complex Event Processing System, Support Vector Machines and Software Engineering.

Dr. Suneel YadavAssistant Professor

Dr. Suneel Yadav is an Assistant Professor in the Department of Electronics and Communication Engineering at the Indian Institute of Information Technology, Allahabad. He has completed his PhD degree in the Discipline of Electrical Engineering at Indian Institute of Technology Indore, Madhya Pradesh, India, in 2016. Dr. Yadav has numerous publications in peer-reviewed journalsjournals and conferences and he is also serving as a reviewer in a number of international journals. His current research interests are in the areas of Physical Layer Security, Wireless Relaying Techniques, Cooperative Communications, Cognitive Relaying Networks, Intelligent Reflecting Surfaces, Device-to-Device Communications, Signal Processing, and MIMO Systems.

Evaluation methodology is the discretion of the faculty. The methodology includes module based assessments, class contribution, capstone project and any other component as decided by the respective course faculties. Additionally, faculty may choose to conduct a pre-assessment prior to the commencement of certain modules, to ascertain participant readiness to progress further. Basis analysis of the pre-assessment, an individual participant may be required to undertake some refresher/self-study on certain basic areas to help better cope and comprehend the program contents.

A minimum of 75% attendance to the live classes is a prerequisite for the successful completion of this program. The program may require participants to work on individual/group assignments and/or projects. The main objective of such assignments/projects will be to help the participants apply their conceptual learning in the program to actual/real life scenarios. Participants who successfully complete the evaluations and satisfy the requisite attendance criteria, will be awarded a certificate of completion. Participants who are unable to clear the evaluation criteria but have the requisite attendance will be awarded a participation certificate.

Assessment

The delivery would comprise a judicious mix of live virtual lectures, discussions, case studies and experience sharing through peer discussions. The course design is oriented to facilitate learning through association of the various management concepts and its application in the business world. Across different modules, participants may be encouraged to apply or relate their in-class learning to live situations at work, peer learning therefore would be a key pillar of the process. Take-home projects may be assigned in certain modules.

All enrolled students will also be provided access to our SLIQ Cloud Campus through which they may access other learning aids, reference materials, assessments, case studies, projects and assignments as appropriate. Throughout the duration of the course, students will have the flexibility to reach out to the professors, real time during the class or offline via our SLIQ Cloud Campus to raise questions and clear doubts.

Pedagogy

Established in 1999 as a center of excellence in Information Technology and allied areas, Institute was conferred the Deemed University status by Govt. of India in the year 2000.

In 2014 the IIIT Act was passed, under which IIITA and four other Institutes of Information Technology funded by the Ministry of Human Resource Development were classed as Institutes of National Importance. Recently, IIITA Prayagraj has instituted the Centre for Short Term Certification Programmes (CSTCP) with the primary aim of conducting online courses through suitable online platforms provided by various companies.

IIIT-Allahabad was ranked 119 in BRICS nation by the QS World University Rankings of 2019. Among government engi-neering colleges in India, IIIT-Allahabad ranked 10th by India Today in 2019[9] and 18 by Outlook India in 2019. It was ranked 82 among engineering colleges by the National Institutional Ranking Framework (NIRF) in 2019. IIIT-A is very famous for its placements and coding culture.

Program Details

Program Commencement: 27 June 2021

Duration: 12 Months

Schedule of classes: Sundays from 10.00 a.m. to 01.15 p.m. IST

Program Fee:

For Indian Participants: INR 2,00,000 + GST

For International Participants: USD 4000Attractive Financing Options including Interest Free Loans available. Conditions apply*

About Institute

For More Details

Visit- www.talentedge.comWrite in to- enquiry.dtd@talentedge.in

Call at +91 - 8588819933