Artificial Intelligence Beyond Theory & Concepts - Our AI Summer Academy Empowers Silicon Valley School Students to AI Innovation - Free Two Day Event

Artificial Intelligence for Schools
Beyond Theory
AI
Big
Data
IIoT
© DeepSphere AI Community | Confidential & Proprietary
AI Summer Academy
Community Service
July 14 & 15, 2018
Fremont
Free Two Day
Event

Enabling Silicon Valley Schools for the
Digital Age
Our AI Summer Academy
Empowers 100+ Students to
AI Innovation
o Dougherty Valley
o WHS
o Moreau Catholic
o Mission San Jose High
o Washington High
o Irvington High
o American High
o San Marin High
o Fallon Middle
o Cupertino High
o California High
o Foothill High
o Sierramont Middle
o Saint Francis
o Basis Independent
o Dublin High
o San Ramon Valley High
o Mountain house High
o Cupertino High
o Horner Junior High
o Harker
o Wilcox High
o Santa Teresa High
o Thornton Junior High
o Thomas Russell Middle
o Milpitas High
o St Francis High
o DVHS San Ramon
o Hopkins Jr
Students
Demographic
Free Two Day
Event
July 14 & 15, 2018
Fremont

Content
o Learning Objective
o Venue & Date
o Learning Roadmap
o Session Schedule
o Lab Work
o Key Takeaways
o Program Designer
o Appendix
o Session Details
o Industry Solutions
o AI Platform
o Registration
o Team
Two Days AI Program for Schools
“Jothi..I am honored to learn from your comments
and messages in the MIT Sloan & CSAIL course... "
Student
MIT Sloan & CSAIL
July 14 & 15, 2018
Fremont
Free Two Day
Event

Community Service for Schools
This is not a sales and marketing material and we are not promoting any products or services.
This two day AI boot camp is to educate San Francisco Bay area school students, along with BATM (Bay Area Tamil
Manram), a non profit organization. We are committed to bringing deeper knowledge of Artificial Intelligence to San
Francisco Bay Area school students. Our goal is to go beyond AI concepts by demonstrating the practical use of
Artificial Intelligence to school students, and by stimulating innovative ideas and thoughts to solve real-world industry
problems using Artificial Intelligence techniques. We also want to educate students to the role of AI in the future, and
the impact of AI to society, business, technology and government policy and guidelines.
This content has been developed with a focus to build hands-on AI competency in order to meet the market demand
and industry needs. We are sharing some of our work with students to bring awareness about the steps, processes and
technologies that are required to solve industry problems using Artificial Intelligence.
This is an ongoing event and we will be hosting this event once every three months, free of cost. As there are always
opportunities for improvement, we are looking forward to receiving feedback and comments.
Jothi Periasamy, AI Community Contributor

Where are we?
o There are 1000’s of AI presentations
and publications on general AI
concepts, ideas and vision, but none
of them show step by step directions
on how to apply AI techniques to
optimize a business process or
improve productivity. Most are at an
abstract or scientific research level.
o Learning for information is different
than learning for solving practical
business problems. To solve real
business problem using AI
techniques we need to go beyond AI
concepts and AI research.
We are sharing our view on enterprise AI after seeing hundreds of AI presentations and having spoken at
several AI conferences. We wonder how people can talk about enterprise AI without deep understanding of
the enterprise AI framework and the steps involved to deliver AI value to business.
Beyond AI Theory and Concepts
What do we need?
o Enterprise AI cannot be built by
knowing AI concepts without deeply
understanding business process,
business data and existing legacy
technologies.
o Data engineering plays a significant
role in implementing enterprise AI.
There is no way to build enterprise AI
without making Big Data, IIoT
(Industrial Internet of Things) and AI
work together
How do we get there?
o If your goal is to solve mainstream
business problems using AI
techniques such as ML, DL, NLP and
RPA, then you need practical
problem solving expertise, including
deeper business process knowledge,
hands-on Big Data and IIoT platform
know-how and AI platform expertise.

Learn to Lead
Lead to Innovate
AI
Objective

Industry
o Our program brings industry view to academic concepts and demonstrates practical business problem-
solving techniques and approach through proven industry use cases.
o Our in-depth program addresses skills and expertise that’s lacking to translate complex industry
problems into AI solutions using machine learning and data capabilities.
o Our program, enabled through advanced computing platform, makes AI, IIoT, and big data technologies
work together seamlessly.
© DeepSphere, Inc. | Confidential & Proprietary
Academy Technology
We Connect Academy, Industry & Technology Together

o Day One
o Day Two
Saturday, the 14th
of July 2018
Sunday, the 15th
of July 2018
43225 Mission Blvd,
Fremont, CA 94539
Date Venue
Students
Demographic
9AMPST–5PMPST
Date and Venue
o San Jose
o Santa Clara
o San Ramon
o Newark
o Pleasanton
o Dublin
o Novato
o Newark

Learning Roadmap
o Artificial Intelligence and Data Concepts
o Industry Challenges and AI Needs
o AI Implementation Framework and Use Cases
o Technology - Artificial Intelligence and Data
Machine
Learning
Deep
Learning
NLP
Big
Data
IIoT
Python &
Predictive Model
o Participant Group Project
RoadmapRoadmapRoadmap
Hands-onSession

Session Schedule | Day One
Session # Date & Time Session Agenda Session Topics
1 07/14/2018
09:00 AM -11:00 AM
Artificial Intelligence Defined
o Concepts
o Academic Perspective
o Industry Perspective
o Technology Perspective
2 07/14/2018
11:15 AM -12: 45 PM
Artificial Intelligence Implemented
o Concepts
o Demo
o AI Implementation Framework
o Problem Statement
o Machine Learning
o Deep Learning
o Natural Language Processing
o Robotic process Automation
o Computer Vision
3
07/14/2018
01:15 AM -02: 45 PM
Artificial Intelligence Applied in HR
o Real-life Implementation
o Demo
o Model Selection
o Model Implementation
o Data Engineering
o Model Testing
o Model Deployment
4
07/14/2018
03:00 AM -04 45 PM
Artificial Intelligence Applied in Health
o Demo
o Model Selection
o Data Engineering
o Model Testing
o Model Deployment
15 Min Break
30 Min Break
15 Min Break

Session Schedule | Day Two
Session # Date & Time Session Agenda Session Topics
5 07/15/2018
9:00 AM -11:00 AM
Role of Data in AI
o Big Data
o IIoT (Industrial Internet of Things)
o Relationship Between AI & Big Data
o AI vs. Big Data vs. IIoT
o Big Data Management
o Big Data Engineering
6 07/15/2018
11:15 AM -12: 45 PM
Impact of AI
o People
o Business
o Technology
o Impact vs. Opportunities
o Societal Impact
o New Policies & Operating Model
o New Skill Development
o New Products & Services
o New Technology Adoption
7 07/15/2018
01:15 AM -02: 45 PM
Students Group Project o Business Challenges and Need for AI
o Business Justification of AI
8 07/15/2018
03:00 AM - 04: 45 PM
Students Group Project Presentation o Industry and Problem Selection
o Business Values - Quantitative & Qualitative
9 07/15/2018
04: 45 PM – 5:45 PM
Key Takeaways o Future of AI and Education
o Next Steps for Students
o Skill Development
o Advanced Learning & Problem Solving
15 Min Break
30 Min Break
15 Min Break

Session Schedule | Lab Work
Lab Session # Date & Time Lab Agenda Lab Focus Area
1 07/14/2018
11:15 AM -12: 45 PM
Artificial Intelligence Development Infrastructure
o Setting Up Development Environment
o Anaconda - Conda, NumPy & Sympy
o Python
o Jupyter Notebook and/or Spyder
o Spark MLIB
o TensorFlow & Scikit-learn
2 07/14/2018
01:15 AM -02: 45 PM
o Model Testing
o Model Deployment
o Jupyter Notebook
o Spyder
o Scikit-learn
3 07/15/2018
01:15 AM -02: 45 PM
Students Group Project
o Model Testing
o Model Deployment
o Jupyter Notebook
o Spyder
o Scikit-learn
o In this short-term course, we will not be able to spend more time in lab work and advanced lab work.

Key Takeaways
Participants will gain hands-on knowledge from concept to realization
1 2 3 4
Deeply
Understand
how AI is
applied in
business
processes
Learn the
framework to
implement AI
to solve real-
world
problems
Gain
practical
skills and
on-the-job
learning
experience
In-Depth
learning of data
engineering
and AI
technologies

Jothi Periasamy,
Instructor
o 17+ years of management consulting and end-to-end AI (ML, DL, RPA, NLP)
experience with Sierra Infosys, Inc. Deloitte, E&Y, and KPMG
o Over 50+ clients across industries: Health, Energy, Oil & Gas, Consumer
o Teaches AI at MIT – Head of AI, Architect at Experfy, Harvard Innovation Lab
o Co-innovates industry solution along with SAP America
o Published on finance, AI, big data, IIoT, Cloud, and SAP Appliances
o Delivered many research projects on market for AI enterprise services
o Globally recognized as a keynote speaker. Spoke at 50 conferences
o Recently invited by Prime Minister office of Dubai, Malaysia, and Montreal
“…I just love working with Jothi…”
CFO Office
Procter and Gamble
“…Jothi, I am counting on you for SAP HANA enablement …”
Head of HANA Innovation
SAP America

Stanford
Alumni
Harvard
PhDs
MIT
Learning
Facilitator
Industry
100+ Customers
Engagement
Public Services
Oil & Gas
Energy
Health
Consumer
Program Designer
Stanford Alumni, Harvard PhDs, MIT learning facilitator and leading management consulting expertise at
Deloitte, E&Y and KPMG with proven customer engagements.

Appendix
o Session Details
o Industry Solutions
o AI Platform
o What You Learn?
July 14 & 15, 2018
Fremont

Day Date & Time Session
Agenda
Session
Topics
Industry | Business
Learning Topics
Technology
Learning Topics
1 07/14/2018
9:00 AM -11:00 AM
Artificial Intelligence Defined
o Concepts o Academic Perspective
o Industry Perspective
o Technology Perspective
o Business Alignment
o AI Applied in Health
o AI Applied in Consumer
o AI Applied in Energy
o AI Applied in Oil & Gas
o Role of Technology in AI
o Hardware
o Software
o Data Technology
o Programming
15 Min Break
1 07/14/2018
11:15 AM -12: 45 PM
Artificial Intelligence Implemented
o Concepts
o Demo
AI Implementation Framework
o Problem Statement
o Machine Learning
o Deep Learning
o Robotic process Automation
o Computer Vision
Problem Statement
o Business Process
o Business Values
o Productivity
o Cost
o Revenue
Technical Architecture
o Legacy Technology - SAP & Oracle
o Jupyter Notebook
o Spyder
o Spark MLIB,
o TensorFlow & Scikit-learn
o Data - Hadoop Ecosystem
30 Min Lunch Break
1
07/14/2018
01:15 AM -02: 45 PM
o Demo
o Model Selection
o Data Engineering
o Model Testing
o Model Deployment
o Skill Development
o Job Description
o Candidate Identification
o Profile Development
o Top Ten Candidates
o Classification – Text/Sentence
o Language Modeling
o Machine Translation
o Speech Recognition
15 Min Break
1
07/14/2018
03:00 AM -04 45 PM
Artificial Intelligence Applied in Health
o Demo
o Model Selection
o Data Engineering
o Model Testing
o Model Deployment
o Health Risk
o Length of Stay
o Readmission Rate
o Health Monitoring
o Random Forest
o K-Means Clustering
o LDA
o Logistics Regression
o Gradient Boosted Decision Tree
Session Details

Day Date & Time Session
Agenda
Session
Topics
Industry | Business
Learning Topics
Technology
Learning Topics
2 07/15/2018
9:00 AM -11:00 AM
Role of Data in AI
o Big Data
o IIoT (Industrial Internet of Things)
o Relationship Between AI & Big Data
o AI vs. Big Data vs. IIoT
o Big Data Management
o Big Data Engineering
o Internal Business Data
o External Data
o
o Hadoop Ecosystem
o Sensors Technologies
o Machine to Machine Communication
o Data Engineering Technologies
15 Min Break
2 07/15/2018
11:15 AM -12: 45 PM
Impact of AI
o People
o Business
o Technology
o Impact vs. Opportunities
o Societal Impact
o New Policies & Operating Model
o New Skill Development
o New Products & Services
o New Technology Adoption
o Redefined Business Processes
o Productivity
o Roles & Responsibilities
o Cost & Revenue
o Changes in
o Application Development
o Product Development
o Software Development
30 Min Lunch Break
2
07/15/2018
01:15 AM -02: 45 PM
Group Project o Business Challenges and Need for AI
o Business Justification of AI
o Business Case
o Business Values
o Implementation Roadmap
o Technology Selection
o Data Selection
o Model Selection
15 Min Break
2
07/15/2018
03:00 AM - 04: 45 PM
Group Project Presentation o Industry and Problem Selection
o Business Values - Quantitative & Qualitative
o Business Alignment
o Problem Statement
o Implementation Roadmap
o AI Implementation Framework
o AI Technologies
o Data Engineering Technologies
o AI Model Selection
2 07/15/2018
04: 45 PM – 5:45 PM
Key Takeaways for Students o Future of AI and Education
o Next Steps for Students
o Skill Development
o Advanced Learning
o Problem Solving
Session Details Cont’d.

Prebuilt Models
Industry Solution | Health
Patient Health Risk
Patient Financial Risk
Patient Adherence
Patient Behavioral Patterns
Value Based Care Delivery
Pay for Performance
Readmission Rate
Discharge Rate and LOS
Physician Performance
Financial Forecast and Claims
Fraud Deduction
Case & Disease Management
Lifestyle Monitoring
Fitness Monitoring
Health Monitoring

AI Platform (Sample) Prebuilt Functions
Real-time Data Collector
Devices
Sensors
Big Data Technologies
Enterprise Systems
In-memory Data Integration
Data & Information Model
Integrated Data Sets
Interoperability
SAP S/4 HANA
Oracle BDA
Mycroft BDA
HADOOP & SPARK
Cloud Computing
Machine Learning Libraries
SDK - Python, R, Scala & SQL

Registration
Prepare to Lead
o By text (925) 520-5396
o By email Info@sfbatm.org
o By phone (925) 520-5396
July 14 & 15, 2018
Fremont
Free Two Day
Event

What Will You Learn?
o Enterprise AI
o How AI is Applied in HR Function
o AI Implementation Technology
o AI Model Selection

Business
Platform
Big
Data
Platform
IIoT
Platform
AI
Platform
Beyond AI Theory or AI Research or AI Concepts
Enterprise
AI+ + + =
o Business Process
o Business Data
o Enterprise Technologies
- SAP, Oracle, MS, etc.
Enterprise AI goes beyond AI models, algorithms, and use cases.
Building an enterprise AI model is not as spoken about or presented at conferences, it is quite complex
and requires several different sets of deep skills and expertise.
o Machine Learning
o Deep Learning
o NLP
o RPA & Others

What is an Enterprise AI?
Enterprise
Data
Enterprise
Process
External
Data
External
Process
ex:
Internal
Candidate
Profile
ex:
Internal
Candidate
Assessment
ex:
External
Candidate
Profile
ex:
External
Candidate
Assessment
AI Data Platform Should Interoperate Across External and Internal Data and Technologies such as SAP, Oracle
AI Model Should Interoperate Across Enterprise Business Process - Machine Learning & NLP
There are many different ways to present an enterprise AI but here is how we have been educating our audience about enterprise
AI. An enterprise AI platform, solution, or application should apply AI model and AI techniques on enterprise business process and
enterprise data. An enterprise AI platform should interoperate with existing legacy systems such as SAP, Oracle, Microsoft, IBM
and Open Source technologies.
An enterprise AI is not just building use cases, it should enable business users to realize measurable business values on their day
to day business functions.
Enterprise AI
in HR

b
What is an Enterprise AI?
o Business Process
o Business Data
o Enterprise
Technology
o Measurable
Business Values
o Interoperability
An enterprise AI should work with enterprise business process and collaborate with business
users
An enterprise AI model should be able to utilize enterprise data for self learning
An enterprise AI should interface with existing enterprise legacy technology such as SAP,
Oracle, Microsoft, IBM and Open Source
An ordinary business users should be able to see a measurable value of AI on their day to day
job functions
An enterprise AI platform should be able to connect internal and external business process,
data and technology for self learning.
Key
Characteristics

Human
Intelligence
Artificial
Intelligence
Recruitment
&
Assessment
+ =
Enterprise AI Platform for Global Talent Acquisition
Increase Productivity and Reduce Cost Using Artiﬁcial Intelligence to Augment Human
Intelligence.

Human Resource Problems We Solve
AssessmentRecruitment
o Skill Evaluation - Current & Future
o People Skills
o Behavioral Skills
o Technical Skills
o Educational Skills
o Top Candidate Identification for Next Steps
We are solving the most common HR problems that occur across all organization regardless of the size and
location of an organization.
o Developing Job Description
o Job Posting - Internal and External
o Candidate Identification - Internal & External
o Candidate Skill Matching
o Developing Skill Matrix
o Developing Candidate Profile
Most Common HR Challenges (Few Samples)

How Does it Work?
NLP (Natural Language Processing) Applied in Recruitment
Step
One
Position Approval
Human
Intelligence
Step
Two
Developing Job
Description
Artificial
Intelligence
Step
Three
Candidate
Identification
Internal ( Existing
systems &
Process)
External
Candidate
Internal
Candidate
Artificial
Intelligence
Step
Four
Candidate Profile
Building
Skill Profile
Education
Employment
Publication
Social
Behavior
Criminal
Artificial
Intelligence
Step
Five
Send Top 10
Candidate to the
Recruiter
Artificial
Intelligence
Step
Six
Recruiter to
Finalize Candidate
Human
Intelligence
Step
Seven
Develop Questions
and Answers
Artificial
Intelligence
Step Eight &
Others
Conduct Test &
Send Test Results
and Training
Recommendations
Artificial
Intelligence
o Text Classification
o Language Modeling
o Caption Generation and Machine Translation

Internal Business Data Source
SAP
HANA & HR
SAP Success
Factor
Oracle People
Soft
External Data Source
Job
Portal
Social
Media
Candidate
Portal
o KAFKA - Live Data Streaming
o HDFS - Persistent Data Storage
o ALLUXIO - In-memory Data Processing
o SPARK - Data Provisioning
PYTHON ANACONDA JUPYTER TENSORFLOW SCIKIT LEARN NLTK
o User Interface - Data Visualization
Artificial Intelligence Computing Engine
AI for HR - Architecture (Sample)

HR Process
o Select Job Title
o Develop Skills
o Develop Job Description
o Post Job - Internal & External
o Identify Candidate - Internal &
External
o Develop Candidate Profile
No Model Involved
Will be discussed in the class
o Select Top Ten Candidate Will be discussed in the class
No NLP Involved
AI for HR - Model Selection (Sample)
AI Model
Used
NLP Techniques
Applied

HR Process
o Send Top Ten Candidate for
Approval
o Conduct Assessment
o Send Assessment Outcome
o Develop Recommendation
o Send Recommendation to
Candidate
o Other HR Processes
AI Model
Used
No Model Involved
No Model Involved
NLP Techniques
Applied
No Model Involved
No NLP Involved
AI for HR - Model Selection Cont’d.

More to Learn in the Class …

AI Community Contributor
Mrithula Jothi
AI Developer &
IBP Student
Jean-Jacques Russo
AI Subject Matter Resource
Paula Patel
Buvana Mani
Durga Prasad
Machine Learning Engineer
Balaji Chennakrishnan
Industry Expert - Oil & Gas
Anupama Kuruganti
Data Engineer
Janaki Kowtha
Digital Transformation Resource

AI Community Contributor Cont’d.
Karthikeyan Rajamanickam
Big Data & IIoT Architect
Sankar Janakiraman
Industry Expert - Finance
Pugazendhi Asaimuthu
Data Engineer
Srinivasa Vemula
Sulthan Mohammad
SAP Enterprise Architect
Brian South
Educational Consultant

Thank You !
Jothi Periasamy
AI Community Contributor
(916)-296-0228

Artificial Intelligence Beyond Theory & Concepts - Our AI Summer Academy Empowers Silicon Valley School Students to AI Innovation - Free Two Day Event

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