• Fundamental Cloud Computing
• Introduction to Cloud Storage Service
• Virtualization
• Building a Cloud Server
• Cloud Deploying Environments
• Building a private cloud using lamp & eyeOS
• Cloud Computing at Work
• Cloud Computing Technology Hardware & Infrastructure
• Accessing the Cloud Platforms
• Platform as a Service
• Creating Reports and Dashboards
• Software as a Service
• Infrastructure as a Service
• Introduction to AWS
• Managed Services & Database

Duration : 12 Weeks

Time Commitment: 4 Hrs Per Week

Prerequisites: Computer Networking & basic command in Linux

Credibility Enhancement Awards and Documents:

• 'Console' Certificate
• Microsoft International Certificate (optional)
• Internship/Project Letter (on successful completion of project)

• Module 01: Introduction to Ethical Hacking
• Module 02: Foot printing and Reconnaissance
• Module 03: Scanning Networks
• Module 04: Enumeration
• Module 05: Vulnerability Analysis
• Module 06: System Hacking
• Module 07: Malware Threats
• Module 08: Sniffing
• Module 09: Social Engineering
• Module 10: Denial-of-Service
• Module 11: Session Hijacking
• Module 12: Evading IDS, Firewalls, and Honeypots
• Module 13: Hacking Web Servers
• Module 14: Hacking Web Applications
• Module 15: SQL Injection
• Module 16: Hacking Wireless Networks
• Module 17: Hacking Mobile Platforms
• Module 18: loT Hacking
• Module 19: Cloud Computing
• Module 20: Cryptography

Duration : 12 Weeks

Time Commitment: 4 Hrs Per Week

Prerequisites: Computer Networking & basic command in Linux

Credibility Enhancement Awards and Documents:

• 'Console' Certificate
• Microsoft International Certificate (optional)
• Internship/Project Letter (on successful completion of project)

• Introduction to Deep Learning & Neural Networks
• Multi-layered Neural Networks
• Training ofNeural Networks
• Deep Learning Libraries
• Keras API
• TFLearn API for TensorFLow
• DNN: Deep Neural Networks
• CNN: Convolution Neural Networks
• RNN: Recurrent Neural Networks
• GPU in Deep Learning
• Autoencoders & Restricted Boltzmann Machine (RBM)
• Deep learning applications
• Chatbots Automated conversation bots using one of the descriptive techniques

Duration : 12 Weeks

Time Commitment: 4 Hrs Per Week

Prerequisites: Knowledge in Python Programming

Credibility Enhancement Awards and Documents:

• 'Console' Certificate
• Microsoft International Certificate (optional)
• Internship/Project Letter (on successful completion of project)

Module 1:

• Introduction to Computer Vision
• Different types of Noise and Filtering
• Edge and Features Detection, Feature Matching

Module 2:

• Basic Image Segmentation
• Segmentation Using Clustering Algorithms

Module 3:

• Machine Learning: Supervised and unsupervised Learning

Duration : 12 Weeks

Time Commitment: 4 Hrs Per Week

Prerequisites: No prior experience with computer vision is assumed. A good working knowledge of Programming skills are necessary for these classes. All lecture code and project starter code will be in Python 3/MATLAB 18b.

Credibility Enhancement Awards and Documents:

• 'Console' Certificate
• Microsoft International Certificate (optional)
• Internship/Project Letter (on successful completion of project)

• Introduction to Machine Learning.
• Naïve Bayes
• Decision Trees
• Support Vector Machines
• Decide how to pick the right machine learning algorithm
• Data sets and Questions
• Regressions
• Outliers
• Clustering
• Feature Scaling

Duration : 12 Weeks

Time Commitment: 4 Hrs Per Week

Prerequisites:

• Calculus (taking derivatives)
• Matrix arithmetic
• Probability
• Python coding: if/else, loops, lists, dicts, sets.
• Numpy coding: matrix and vector operations, loading a CSV file

Credibility Enhancement Awards and Documents:

• 'Console' Certificate
• Microsoft International Certificate (optional)
• Internship/Project Letter (on successful completion of project)

• Basics of Python Programming :
• (Looping constructs, Functions, Classes and OOPS concepts)
• Numpy Library :
• Pandas
• Matplotlib and Seaborn
• Exploratory Data Analysis

Duration : 12 Weeks

Time Commitment: 4 Hrs Per Week

Prerequisites: Prior programming experience in any programming language is mandatory.

Credibility Enhancement Awards and Documents:

• 'Console' Certificate
• Microsoft International Certificate (optional)
• Internship/Project Letter (on successful completion of project)

The eminent Prof. (Dr.) Usha Rengaraju Kaggle Grandmaster. Subject Matter Expert for Advance Machine Learning for online master’s program for BITS Pilani (Pilani, Goa, Hyderabad and Dubai ) campus. Prepared the content and the videos for 6-month course in Probabilistic Graphical Models which will be consumed by 20,000 students. Subject Matter Expert for Probabilistic Graphical Models( Advance Machine Learning) for Upgrad. Prepared curriculum which is consumed by 7000+ students. Organized NeuroAI (neuroai.in) which is India’s first ever research symposium in the interface of Neuroscience and Data Science. The event had 19 faculty speakers from premier institutes like MIT, IISC, UMass Boston, IIT Madras, IISER Pune, NBCR Chandigarh, DBS -TIFR Mumbai, NIMHANS Bangalore .Many of them were Shanti Swarup Bhatnagar prize awardees. Chapter Lead for Women in Machine Learning and Data Science (WiMLDS ) Bangalore & Women in Data Science (WiDS) Ambassador for Mysore for 2020. (WiDS is a Stanford University Initiative). She is Editorial Board Member for IJASRW. Presented a talk and workshop in several conferences like PyCon India , ODSC India 2019 , World Machine Learning Summit , DevFest Bangalore, Cochin , Trivandrum and Mysore.Ambassador at JobsForHer and AIMED(connects physicians and data scientists), Volunteer Editor at Humans of Analytics Areas of Expertise : Deep Learning, Machine Learning, Computer Vision, Natural Language Processing, Probabilistic Graphical Models and Data Engineering.

The eminent Prof. (Dr.) Jyoti Gautam is currently working as Associate Professor, CSE Department, JSS Academy of Technical Education NOIDA, U.P., India. Worked as HOD CSE from April, 2015 to May, 2018. Member Executive Committee IWA ( International Water Association, India) 2018-20. Appointed as member of the Governing Council at JSS Academy of Technical Education, NOIDA, Uttar Pradesh, India. Coordinator for Signing of MOU between Xinova, Seattle, USA and JSSATE NOIDA. Invited as a speaker from Japan and Taiwan for one of my research papers on Air Pollution. Invited as a session chair by International Water Association, World Water Congress and Exhibition held in Tokyo as session chair for the Category-Disinfection Products in September 2018. Jury for Smart India Hackathon and World Skills Competition. Published papers in reputed International journals and conferences. Reviewer for journals and conferences of Repute. Attended various conferences, fdps and events.

Ms. Pubali Chatterjee, PhD scholar, University of Calcutta and Senior Research Fellow, CSIR. Also worked as Teaching Assistance at A. K. Choudhury School of I.T. & Department of Applied Physics, University of Calcutta. My area of research is Computer Vision , Machine Learning, Deep Learning, Stochastic Modelling in general along with Medical Image Analysis. I was associated as a Lecturer in different colleges, where I have taken courses on Artificial Intelligence, Data Structure and Algorithm Analysis, Database Management System, Advance Operating System, Digital Image Processing, Machine learning and different programming languages. Also having excellent technical skills on Programming languages like C, C++, MATLAB, Python, SQL, Java Script, HTML, PHP.

Mr. Farman is currently working as a Corporate Trainer. More than two years of experience on Artificial Intelligence/Python/ Machine Learning Technologies in Development. More than three years of experience on Python/ Machine Learning & its Eco-System in Training. Constantly have got a participant satisfaction of more than 92% in all trainings. Gets involved in designing phase of the IT training courses, validates and verifies, trainings imparted and assists in introducing latest technology course and assists in course ware update. Specialized in Python, Java, J2EE, spring, C, C++. Working with Machine Learning and Django. Good analytical skills to find optimal solutions in given constraints. Excellent communication ability both on technical and on client interaction.

Mr. Binayak is an academician and visionary who possesses an excellent leadership in research, teaching, study-material development and has an exceptional delivery record. Close to14 years of experience in the Information Technology Industry as specialized and focused on Corporate Training in the past 5 years. Currently working as a Security Analyst, Corporate and IA trainer on various technologies like VMware® vSphere 5.x & 6.x, Linux, Cloud Computing.