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 (4+)
See all- Microsoft Power BI Bootcamp: Transforming Data to DashboardsLink visible for attendees$298.00
Enroll 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 covers everything from the basics to practical projects. Our hands-on labs ensure you gain real-world experience, and you will leave with the ability to connect to organizational data and create impactful dashboards.
Prerequisites:
- Basic understanding of Databases
Learning Objectives:
- Understand the Power BI ecosystem, including its tools and workflow.
- Extract data from diverse sources such as Excel, CSV, SQL, and the web.
- Master data cleaning and transformation using the Power Query Editor.
- Create reports and visualizations in Power BI Desktop.
- Develop data models with relationships and calculated measures.
- Explore advanced visualizations like maps and custom visuals.
- Utilize filters, slicers, and drill-through options for data exploration.
- Build and format dashboards for effective data storytelling.
- Participate in hands-on project labs to apply your skills.
- Learn about security, app creation, and data connections in Power BI.
Course Outline:
Day-1
Introduction
- What is Power BI?
- What are the Key Tools?
- Typical Workflow
- Power BI Terminology
Extracting Data
- Extracting the data (Excel, .csv, SQL, web)
- Transforming the Data
- Exploring the Power Query Editor
- Applied Steps
- Working With Queries
- Applying Transformations
- Loading Queries
Power BI Desktop Interface
- Report
- Visualizations
- Fields and Filtering
- Formatting and Analytics
Exploring the Data View
- Categorizing Geographical Data
- Formatting Dates
- Controlling Summarization Behavior
Reviewing the Data Model
- What is a Data Model?
- Examine Existing and Creating New Relationships
Measures and Calculated Columns
- Creating Calculated Columns
- Creating simple DAX measures
- Creating a Date Table
- Creating a Dates Table
Day-2
Explore the Visualization Menu
Review a Sample Report
Develop a Report Storyboard
Create and Format Visuals and Pages
- Column and Bar
- Pie
- Adding Pages
- Line
- Matrix
- Formatting Pages
- Maps
- Other Available Visuals
Drill Through Relationships
Using Filters and Slicers
Using Custom Visuals & the Marketplace
- Organizational Visuals
- Additional Page Elements
Create Other Objects in Reports
- Buttons
- Shapes
- Images
- Bookmarks
Publishing the Report
- Establishing a Workspace
- Personal and App Workspaces
Introducing Power BI Service
- App Workspaces
- Create and Format Dashboards
- Get Data
- Update Dashboard
Create and Maintain Apps
- Setting Security
- Finding other Apps
- Connect to organizational data
- Project Labs - Data Science for Healthcare ProfessionalsLink visible for attendees$499.00
Enroll 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.
Data science and digital image processing are becoming an increasingly integral part of health care. This course exposes you to ways data science is used to extract innovative and actionable insights from healthcare-related datasets and medical imaging.
In this course, we will examine how predictive modeling is used to assess outcomes, needs, and potential interventions. We will also explore medical image analysis which has become an inherent part of medical technology.Prerequisites:
Basic Python programming experience
Learning Objectives:
During this course, you will have the opportunity to:- Install Anaconda on a personal computer.
- Prepare and explore healthcare-related datasets using the primary tools for data science in Python (e.g., NumPy, Pandas, Matplotlib, Scikit-learn).
- Examine many of the unique qualities and challenges of healthcare data.
- Understand how data science is impacting medical diagnosis, prognosis, and treatment.
- Use a data-science approach to evaluate and learn from healthcare data (e.g., behavioral, genomic, pharmacological).
- Use deep learning and TensorFlow to interpret and classify medical images.
- Perform feature extraction, segmentation, and quantitative measurements of medical images.
- Understand the increasing importance of data science and image processing in healthcare.
Topic Outline:
- Course Introduction
- Overview of Data Science in Healthcare
- Milestone 1: Install Anaconda/Work with Jupyter Notebooks
- The Data Science Process
- How Data Science is transforming the healthcare sector
- Essential Python Data Science Libraries
- NumPy
- Pandas
- Matplotlib
- Scikit-learn- Data Visualization
- Line Chart
- Scatterplot
- Pairplot
- Histogram
- Density Plot
- Boxplot
- Customizing Charts- Milestone 2: Perform Exploratory Data Analysis of Healthcare Datasets
- Milestone 3: Use Scikit-learn to Apply Machine Learning to Healthcare Questions
- Introduction to Deep Learning for Medical Image Analysis
- Digital Image Processing
- Contrast and Brightness Correction
- Edge Detection
- Image Convolution
- Milestone 4: Use TensorFlow to Interpret and Classify Medical Images
- Conclusion: Next Steps
Structured Activity/Exercises/Case Studies:
- Milestone 1: Install Anaconda/Work with Jupyter Notebooks
- Milestone 2: Perform Exploratory Data Analysis of Healthcare Datasets
- Milestone 3: Use Scikit-learn to Apply Machine Learning to Healthcare Questions
- Milestone 4: Use TensorFlow to Interpret and Classify Medical Images
Date & Time :
11/17/2025: 1-4 PM PST
12/1/2025: 1-4 PM PST
12/8/2025: 1-4 PM PST
12/15/2025: 1-4 PM PST - Machine Learning with Python and LibrariesLink visible for attendees$299.00
Enroll 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 class helps increase awareness about Machine Learning patterns and use cases in the real world, and will help you understand the different ML techniques. Learn about popular ML offerings, and utilize Jupyter Notebooks to perform hands-on labs.
Prerequisite: Basic Python Programming training, or equivalent experience
After this course, you will be able to:
- Describe the role of Machine Learning and where it fits into Information Technology strategies
- Explain the technical and business drivers that result from using Machine Learning
- Describe Supervised and Unsupervised learning techniques and usages
- 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.
- Install and Setup Anaconda.
- Perform hands-on activity using Jupyter Notebooks.
Topic Outline:
Course Introduction- History and background of Machine Learning
- Compare Traditional Programming Vs Machine Leaning
- Supervised and Unsupervised Learning Overview
- Machine Learning patterns
- Classification
- Clustering
- Regression- Gartner Hype Cycle for Emerging Technologies
- Machine Learning offerings in Industry
- Hands-on exercise 1: Install and Setup Anaconda.
- Python Libraries
- NumPy
- Pandas
- Scikit Learn- Hands-on exercise 2: Data Analysis using Pandas
- Algorithms
- Linear Regression
- Decision Tree
- Random Forest
- K-Means Clustering- Hands-on exercise 3: Perform Linear regression using Scikit-learn
- Hands-on exercise 4: Perform Decision tree on Titanic Data set using Scikit-learn
- References and Next steps
- Data Analysis and Visualizations on Tableau ServerLink visible for attendees$198.00
Enroll 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.
Learn the capabilities of Tableau report manipulation and visualization. This class is intended for end users, not developers.
After reserving your spot, you will receive instructions on how to join the live online class via email prior to the day of the class.
Important Note:
This training will be conducted through Tableau Server within a browser, not Tableau Desktop. We will be using Tableau Online, as it has similar functionality and Tableau Server does not have a free trial. This class is intended for end-users, not developers.For Developers interested in using Tableau Desktop, we recommend exploring the other class options, including "Introduction to Tableau Desktop Basics" or "Tableau Desktop Intermediate".
Tableau is a business intelligence tool that allows anyone to easily connect to data, then visualize and create interactive, sharable dashboards. These dashboards are a collection of various views of the data, such as charts, graphs, or summary pivots.
In this class, learn how Tableau Server is used to share and interact with visualizations securely across an organization. This training focuses on interacting with and editing workbooks that have been published to Tableau Server, and is intended for end users, not developers.
By the end of this session participants should feel comfortable working with filters, tabs, sharing, downloading raw data, setting-up favorites, using pause, working with edit mode, and much more.
After a brief once-over of the interface, students will create and manipulate numerous visualizations of the sample data. This session will be a mix of walking through examples with the class and a series of exercises for the student to dig through the data and create a visualization that meets their needs.
Activities and exercises will include but not be limited to:
- Working with filters across tabs
- Setting up subscriptions
- Sharing and downloading visualizations and raw data
- Working with the "pause" button
- Creating visualizations in edit mode
- Navigating between sites, projects, worksheets and dashboards
- Work with charts, graphs, maps and pivots
