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AI-ML Toolkit: Python & Data Science Foundations

  • Case Studies
  • Live Labs: Programming Examples
  • Quizzes
  • Tests: Programming Projects
  • Complete Real-world Applications

Instructor: Dr. Raju Pandey

https: //academy.izen.ai

Email: info@izen.ai

Certificate from Webster University
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AI_Toolkit_Overview

This course is designed to introduce the exciting fields of Artificial Intelligence, Data Science, Machine Learning, and Python programming.

Through engaging lessons, real-world examples, interactive quizzes, and hands-on projects, learners will develop a clear understanding of how data is analyzed, how models are built, and how AI-powered systems work in practice. The course also explores how these technologies are applied across industries and how they are reshaping the future of work and innovation.

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HIGH DEMAND
Job postings related to AI, data science, machine learning, and Python have grown faster than the overall U.S. job market, with demand continuing to rise even during broader hiring slowdowns-making these skills highly attractive to employers.

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HUGE SUPPLY GAP
By 2027, U.S. companies are expected to need more than 1.3 million professionals with AI and data-related expertise, while the current talent pool remains far smaller, potentially leaving nearly half of these roles unfilled without focused upskilling.

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BRIGHT FUTURE
Roles requiring proficiency in AI, machine learning, data science, and Python have expanded significantly in recent years. These positions rank among the fastest-growing in the U.S. job market, giving learners a strong advantage for long-term career growth and advancement.

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  • Skills in AI, Data science, Machine learning, and Python are in rapidly increasing demand—build essential technical knowledge to stay competitive and adaptable in today’s digital economy
  • Gain a solid understanding of core concepts through clear explanations and expert-led instruction
  • Learn how AI and machine learning models are developed and applied using real-world data and Python-based tools
  • Understand practical use cases through industry-relevant examples and case studies
  • Build confidence in working with data, algorithms, and intelligent systems across a wide range of professional roles
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  • Individuals with little to no prior experience in artificial intelligence, data science, or programming
  • Anyone interested in building a strong foundation in AI, machine learning, data analysis, and Python
  • Working professionals, career switchers, and business practitioners seeking a practical introduction to data-driven technologies and their real-world applications
PREREQUISITES:
  • Basic knowledge of programming
  • Basic understanding of statistics would be helpful, though not mandatory
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By the end of this course, you will be able to:

  • Understand the fundamentals of Artificial Intelligence, Data Science, Machine Learning, and Python programming
  • Analyze data and interpret insights using real-world datasets and Python-based tools
  • Learn how machine learning models are built, trained, and applied in practical scenarios
  • Explore industry use cases to see how AI-driven solutions are transforming businesses and careers
  • Build confidence in working with data, algorithms, and data-driven decision-making

This certificate program course, to help you develop expertise in Machine Learning.

AI-ML Toolkit: Python & Data Science Foundations

Python has become the de facto standard for developing ML applications. This course provides a system and design-driven view of Python, data analysis, and visualization tools, and the ML learning framework. This course will also provide the necessary background on statistics.

  • Natural Intelligence and Types of Intelligence
  • Definitions
  • History of AI
  • Elements and classification of AI
  • Applications of AI and Why should you learn AI?
  • ML vs. Traditional systems
  • Evolution
  • Implications and Future of AI
  • Matrices
  • Functions and Data Analysis
  • Data and Types
  • Control Flow
  • Functions
  • Object Oriented Programming
  • Modules & Packages
  • Representation of data as Matrices
  • Vectors and Sequences
  • Indexing & Slicing
  • Transformation
  • Operations on Arrays
  • Read and store data in different formats (CSV, XLS, TXT, JSON, etc)
  • Series and Data Frames
  • Indexing
  • Operations
  • Handling Unknowns
  • Sorting
  • Storage
  • Introduction to Data visualization
  • Charts
  • 3D Plots and Contours
  • Introduction to ML-framework
  • Estimators
  • Dataset libraries
  • Basics and Types of Data
  • Data Preparation
  • Categorical Data
  • Data Normalization
  • Data Analysis
  • Feature Engineering
  • Cost and Error Analysis
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PROGRAM FACULTY

Dr. Raju Pandey is a Professor Emeritus in the Computer Science department at the University of California at Davis, where he developed and taught graduate and undergraduate courses in programming languages, operating systems, distributed systems, Internet of Things, Wireless sensor networks, Web-based systems, and compilers.

He is also the CEO and founder of Thinking Books, a software Infrastructure and Tools company.

Dr. Pandey has a deep interest in math and computer science education and has developed novel interactive methods and tools for teaching both algorithmic and system aspects of Computer Science courses.

  • Dr. Pandey’s first startup, SynapSense, was a pioneering IoT company, later acquired by Panduit.
  • His research and entrepreneurial interests lie in AI, Programming Languages, Blockchain, Internet of Things, Cloud, Security, and Privacy. Specifically, his interests are driven by the need to build software systems that are easier to build, analyze and deploy.
  • In this regard, he has developed a novel software platform for building multi-platform AI, Blockchain, Mobile, and IoT applications. The platform includes a next-generation programming language, Ankur, that Dr. Pandey has designed and implemented. The platform will enable development of AI applications in which both algorithm-driven (deterministic) and data-driven (non-deterministic) components of AI applications can be integrated seamlessly.
  • In addition, he consults extensively with companies on AI, Blockchain, IoT, Cloud, Mobile Computing, and Distributed Systems.
  • He has published 40+ papers in conferences and journals and holds 16+ patents in software, visualization, wireless networks, data analytics, security, and control systems.
  • Dr. Pandey holds a B.Tech. degree in Computer Science from IIT (Indian Institute of Technology), Kharagpur, and Ph.D. in Computer Science from the University of Texas at Austin.
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  • Online using desktop, laptop or mobile devices
  • Learn at your own convenient time, and pace
  • Video lectures delivered from a cloud LMS platform
  • Quizzes are given remotely
  • Hands-on projects, and industry case studies for the reinforcement of the learning
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  • 12 weeks, around 10 hours per week, or a total of 120 hours
  • Rolling enrolment allows you to start the course any time. The duration can aligned to your requirements.
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