What we’re about
* What your Meetup Group is about?
The focus of this Meetup group is to foster knowledge in the area of Big data and AI/ML/DL. Our goal is to share and educate people on varied topics within the Big data and Artificial Intelligence space.
* Who should join: Describe your ideal members?
Software Professionals - Anyone curious and interested in learning about Big data and AI/ML/DL.
It would range from people who are just curious George to folks who want to take Big data as profession/career.
Most of the sessions would be Webinar so location should not be a constraint for people to join.
* Why they should join: To learn, share, or have fun
Our passion is to help the world be more informed through these knowledge sharing and education sessions
* What members can expect: Describe typical activities that will foster in-person, face-to-face connections
This group is to foster learning of Big data and Artificial Intelligence technologies.
Upcoming events
6
- $199.00
•OnlineNon-techie Starter Series - AI & Data Science
OnlineEnroll in this training and receive a one-month complimentary e-learning subscription with access to 40+ courses.
This course is provided by Big Data Trunk for Stanford Technology Training Program but a limited few seats available to the public.
Students of this class may have opportunity to be considered for Internship with Big Data Trunk.
This course for non-tech professionals seeking a foundational understanding of AI and Data Science. It covers key concepts and terms in an easily comprehensible manner. No programming or tech expertise needed.
The course will begin with an introduction to AI and Data Science, including an overview of the field and its potential applications. We will explore different types of data and how they are collected, as well as the importance of data quality and how to clean and preprocess data.
Throughout the course, you will be provided with real-life examples of how AI and Data Science are used in different industries. There will be a discussion on the limitations and ethical considerations of using data and explore future trends in AI and Data Science and their potential impact.
Audience
This course is designed for professionals in HR, finance, marketing, operations, or any other non-technical field who want to stay up to date with the latest developments in AI and Data Science and leverage them to drive business value.
Prerequisites/Professional Experience
Understanding of how computers work.
Learning Outcomes
By the end of this course, participants will have gained a foundational understanding of AI and Data Science and will be able to apply this knowledge in their own work and decision-making.
Course Topics
Introduction to AI and Data Science
- What is Data Science and why is it important?
- An overview of the Data Science process and its components
- Common terminologies in AI and Data Science and what they mean
Applications & Trends of AI and Data Science
- Real-life examples of how Data Science is used in different industries
- Understanding the limitations and ethical considerations of using data
- Future trends in Data Science and its potential impact
1 attendee - $299.00
•OnlineArtificial Intelligence and Machine Learning Basics (Non Programmers)
OnlineEnroll in this training and receive a one-month complimentary e-learning subscription with access to 40+ courses.
This course is provided by Big Data Trunk for Stanford Technology Training Program but a limited few seats available to the public.
Students of this class may have opportunity to be considered for Internship with Big Data Trunk.
This course provides a fun and non-technical introduction to Artificial Intelligence and Machine Learning. It provides the vocabulary and basics for this exciting new world.
Prerequisite: Basic programming knowledge preferred
This Artificial Intelligence (AI) and Machine Learning (ML) class helps in awareness about AI and ML patterns and use cases in real world. You will get an understanding of ML concepts like Supervised and Unsupervised learning techniques and usages. We will discuss the difference between AI vs ML vs Deep Learning (DL) along with usage patterns. We will help you expand your vocabulary in AI to understand techniques like Classification, Clustering and Regression. Finally, we would do a ML demo to illustrate few tools and next steps.
In this course, you will have an opportunity to learn how to:
- Describe Supervised and Unsupervised learning techniques and usages
- Compare AI vs ML vs DL
- Understand techniques like Classification, Clustering and Regression
- Discuss how to identify which kinds of technique to be applied for specific use case
- Understand the popular Machine offerings like Amazon Machine Learning, TensorFlow, Azure Machine Learning, Spark mlib, Python and R etc.
- Understand the relation between Data Engineering and Data Science
- Understand the Data Science process
- Discuss Machine Learning use cases in different domains
- Identify when to use or not use Machine Learning
- Define how to form a ML team for success
- Understand usage of tools through a ML Demo and hands-on labs.
Topic Outline:
- Course Introduction
- History and background of AI and ML
- Compare AI vs ML vs DL
- Describe Supervised and Unsupervised learning techniques and usages
- Machine Learning patterns
- Classification
- Clustering
- Regression- Gartner Hype Cycle for Emerging Technologies
- Machine Learning offerings in Industry
- Discuss Machine Learning use cases in different domains
- Understand the Data Science process to apply to ML use cases
- Understand the relation between Data Engineering and Data Science
- Identify the different roles needed for successful ML project
- Hands-on: Create account for Microsoft Azure Machine Learning Studio
- Demo: ML using Azure ML studio
- Demo: ML using Scikit-learn
- References and Next steps
Date & Time:
2/11/2026 :9-12 pm pst.
2/12/2026 :9-12 pm pst.1 attendee
Past events
218
Group links
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