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AI Training Program

Artificial Intelligence for Non-Programmers 

You will master the fundamentals of data science, machine learning, and artificial intelligence in this instructor-led, practical training program. The course is divided into two sections: theoretical and practical. Students will gain practical problem-solving skills during the course while studying topics including healthcare, the stock market, banking, manufacturing, and other sectors. Students who complete the program will have the hands-on experience necessary to expand their knowledge of machine learning and AI and work on cutting-edge AI projects like self-driving cars and predictive maintenance. At the end of this course, you will develop a portfolio to showcase your knowledge, experience, and skillset.

QuantaHub2 Training Center

Who can learn from this course?
This program is designed for:

  • Government employees or contractors who are looking to gain Artificial Intelligence skills as a part of meeting agency AI requirements.

  • Enabling technical resources to rapidly build and enhance Analytical and AI models without writing time consuming code.

  • Working professionals requiring skill upgrade.

Program Details:

  • Duration – 20 hours (Lecture – 10 hours, Lab – 10 hours)

  • Mode of Training – Instructor led sessions (online)

  • Requirement – Laptop and Internet connection

Tools Covered:

Momentum Platform

  • Data Engineering

  • MLOps

  • Automate

  • Impulse Data Warehouse

  • Inset BI

Key Takeaways:

  • Certificate of Internship

  • Letter of Recommendation (upon request)

Module 1 – Data Engineering

  1. Fundamentals

  2. Data Sources and Types

  3. Data Transformation

  4. SQL in Data Transformation

  5. Data Pipeline & Warehousing

  6. Exploratory Data Science

  7. Assessment

Module 2 – Machine Learning

  1. Fundamentals

  2. ML Algorithms

  3. Usage Scenario

  4. Feature Engineering

  5. Supervised ML Algorithms

  6. Classification

  7. Regression

  8. Deep Learning and Neural Networks

  9. Unsupervised ML Algorithms

  10. Recommendation Engineering

  11. Prediction and Testing

  12. Model Deployment

  13. Assessment

Module 3 – MLOps

  1. Introduction

  2. Components

  3. ML Continuous Integration and Continuous Deployment (CI/CD) Pipeline

  4. Model Deployment

  5. Model Monitoring

  6. Data Drift Detection

  7. Model Governance

  8. Assessment

Module 4 – Computer Vision (CV)

  1. Introduction

  2. Computer Vision Pipeline

  3. ML Algorithms used in CV

  4. Convolutional Neural Networks (CNN)

  5. R-CNN, Fast R-CNN, Faster R-CNN

  6. Single Shot Multi-Box Detector (SSD)

  7. You Only Look Once (YOLO)

  8. Assessment

Module 5 – Visualization and BI

  1. Introduction to BI

  2. Visual Data Exploration

  3. Charts and Graphs

  4. Developing Dashboards

  5. Designing Reports

  6. Designing Alerts

  7. Security and Governance

  8. Assessment

Module 6 – Use Cases

  1. Use Case Selection 

  2. Problem Statement to Solution Steps

  3. Developing Use Cases

  4. Visualizing Outcomes

  5. Assessment

About the Trainer

Shamshad (Sam) Ansari

Sam Ansari - Trainor and Professor at GMU

Shamshad (Sam) Ansari is a distinguished data scientist, inventor and author. Sam currently serves as an Adjunct Professor at George Mason University, teaching graduate-level programs within the Data Analytics Engineering department of the Volgenau School of Engineering. His areas of instruction encompass machine learning, natural language processing, and computer vision, where he imparts his knowledge and expertise to aspiring professionals.

He is the author of the very popular book "Building Computer Vision Applications using Artificial Neural Networks". He is also the founder, president and CEO of

Accure, an AI automation company and Partner of QuantaHub2. He enjoys working with software engineers, data scientists, devops, and business analysts, and solving real-world scientific and business problems.

He has worked with 4 tech startups in his 20+ years of career. Prior to starting Accure, he worked for Apixio, a healthcare AI startup, IBM, and Orbit Solutions. He has technical expertise in the area of computer vision, machine learning, AI, cognitive science, NLP, and big data. He architected, designed, and developed an AI automation platform, called Momentum, that allows to build AI solutions without writing code. He is passionate about teaching and mentoring.


He has spent more than 10,000 hours in teaching and mentoring students from across the world. Sam holds a bachelor's degree in engineering from BIT Sindri and Master's degree in computer science from Indian Institute of Information Technology and Management (IIITM) Kerala.

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