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- User Authentication
- Keerthana Subramanian's Credentials
- Keerthana Subramanian's Wallet
- Data Science Tools
- The Four Vs of Data
- Estimates & Measures
- Introducing SELECT Statement Queries
- Communication & Database Security
- Data Communication & Visualization
- AWS Cloud Practitioner 2023: Benefits & Design Principles of the AWS Cloud
- Predictive Analytics: Identifying Tumors with Deep Learning Models
- Reimagining the Customer Experience with Generative AI
- Unlocking Business Solutions with AI-Powered Analytics
- Data Engineering on Microsoft Azure: Storage Accounts
- Data Engineering on Microsoft Azure: Designing Data Storage Structures
- Data Silos, Lakes, & Streams Introduction
- Data Lakes on AWS
- Data Lake Sources, Visualizations, & ETL Operations
- Simple Descriptive Statistics
- R Classification & Clustering
- R Regression Methods
- Data Exploration using R
- Apache Spark Getting Started
- CGI Annual Tour F2025
- Leading in the Age of Generative AI
- Getting Started with Power Query in Power BI
- Track 1: From Data Loading to Stunning Visualizations
- Final Exam: From Data Loading to Stunning Visualization
- Data Loading & Visualization in Power BI: Data Modeling
- Data Loading & Visualization in Power BI: Advanced Visualizations
- Data Loading & Visualization in Power BI: Loading Data from Cloud Storage
- Data Loading & Visualization in Power BI: Loading Data from Databases
- Linear Regression Models: Multiple & Parsimonious
- Data Warehouse Essential: Architecture Frameworks & Implementation
- Developing an AI/ML Data Strategy: Data Management & Governance in AI
- Data Integration
- Building ML Training Sets: Preprocessing Datasets for Linear Regression
- Developing an AI/ML Data Strategy: Building an AI-powered Workforce
- Azure Data Scientist Associate: Machine Learning
- Data Loading & Visualization in Power BI: Getting Started
- Predictive Analytics: Detecting Kidney Disease Using AI
- Generative AI and Its Impact to Everyday Business
- Establishing AI Guardrails and Governance
- Expert Insights on Strategic Thinking
- Expert Insights on Ethics
- Using Strategic Thinking to Consider the Big Picture
- Expert Insights on Mindsets
- Building Personal Power through Influence
- Personal Power and Credibility
- Taking the Lead with Workplace Motivation and Engagement
- Maximize Your Productivity by Managing Time and Tasks
- Data Engineering Getting Started
- Importing & Exporting Data using R
- R Data Structures
- Data Architecture Getting Started
- Linear Models & Gradient Descent: Gradient Descent and Regularization
- Building ML Training Sets: Introduction
- Linear Algebra and Probability: Fundamentals of Linear Algebra
- NLP for ML with Python: NLP Using Python & NLTK
- CGI Annual Tour F2024: Asia Pacific Global Delivery Centers of Excellence (retired October 2023)
- Expert Insights on Discovering Your Strengths
- Predictive Analytics: Case Studies on Predictive Analytics for Healthcare
- Developing an AI/ML Data Strategy: Data Analytics & Data Ethics
- Developing an AI/ML Data Strategy: The Data Analytics Maturity Model
- Selenium Deep Dive: Setting Up Selenium for Automated Testing
- Linear Regression Models: Introduction to Logistic Regression
- Python Unit Testing: Advanced Python Testing Using the unittest Framework
- Preparing & Cleaning Data in Tableau Desktop
- Tableau Desktop: Real Time Dashboards
- Data Collection & Exploration
- Data Exploration
- Data Analysis Concepts
- Math for Data Science & Machine Learning
- Data Transformation
- Clustering, Errors, & Validation
- Data Preprocessing
- Predictive Modeling: Implementing Predictive Models Using Visualizations
- Predictive Modeling: Predictive Analytics & Exploratory Data Analysis
- Applying Predictive Analytics
- NLP for ML with Python: Advanced NLP Using spaCy & Scikit-learn
- Clustering Techniques
- Functions in Python: Working with Advanced Features of Python Functions
- Data Science Statistics: Applied Inferential Statistics
- Linear & Logistic Regression
- Linear Regression Models: Building Models with Scikit Learn & Keras
- Data Reduction & Exploratory Data Analysis (EDA)
- AWS Certified Machine Learning: Data Engineering, Machine Learning, & AWS
- Functions in Python: Gaining a Deeper Understanding of Python Functions
- Text Mining & Social Network Analysis
- Scalable Data Architectures: Using Amazon Redshift & QuickSight
- Python Classes & Inheritance: Getting Started with Classes in Python
- Data Visualization: Getting Started with Plotly
- Python Classes & Inheritance: Advanced Functionality Using Python Classes
- Python Fundamentals Bootcamp: Session 4 Replay
- Complex Data Types in Python: Shallow & Deep Copies in Python
- Conditional Statements & Loops: Advanced Operations Using for Loops in Python
- Machine & Deep Learning Algorithms: Regression & Clustering
- Machine & Deep Learning Algorithms: Introduction
- Machine & Deep Learning Algorithms: Data Preparation in Pandas ML
- Data Filtering
- Data Structures & Algorithms in Python: Fundamental Data Structures
- Conditional Statements & Loops: The Basics of for Loops in Python
- Data Structures & Algorithms in Python: Trees & Graphs
- Python Fundamentals Bootcamp: Session 2 Replay
- Getting Started with Python: Introduction
- Data Structures & Algorithms in Python: Implementing Data Structures
- Python Basics
- Conditional Statements & Loops: While Loops in Python
- Functions in Python: Introduction
- Conditional Statements & Loops: If-else Control Structures in Python
- Time Series Modeling
- Complex Data Types in Python: Working with Dictionaries & Sets in Python
- Complex Data Types in Python: Working with Lists & Tuples in Python
- Python Development: Creating Classes, Handling Errors, & Importing Modules
- K-Nearest Neighbor (k-NN) & Artificial Neural Networks
- SELECT Statement, Expressions, & Operators
- Relational Database Concepts
- New Developments in Python
- Data Gathering
- Raw Data to Insights: Data Ingestion & Statistical Analysis
- Python - Using Pandas to Work with Series & DataFrames
- Linear Regression Models: Introduction
- Data Science Statistics: Using Python to Compute & Visualize Statistics
- Inferential Statistics
- Common Approaches to Sampling Data
- Python - Pandas Advanced Features
- Python - Using Pandas for Visualizations and Time-Series Data
- Python for Data Science: Advanced Data Visualization Using Seaborn
- Python - Advanced Operations with NumPy Arrays
- Python for Data Science: Basic Data Visualization Using Seaborn
- Python - Manipulating & Analyzing Data in Pandas DataFrames
- Correlation & Regression
- Python - Introduction to NumPy for Multi-dimensional Data
- Python - Introduction to Pandas and DataFrames
- Model Development, Validation, & Evaluation
- Process & Applications
- Data Science Overview
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