View upcoming live classes and sessions for our active cohorts.
Detailed session on Introduction to Apache Airflow
Detailed session on Conditional Routing & Logic
Break Week - No Classes
Detailed session on Random Forests & Ensemble Learning
Image Classification with CNN; Sequential Data with Recurrent Neural Networks; LSTM; GRU; Limitations of RNNs and LSTMs
Break Week - No Classes
Gaussian processes, acquisition functions, Optuna trials, AutoML with TPOT — tune XGBoost and compare.
Break Week - No Classes
Break Week - No Classes
Introduction to Data Visualization; Selecting Appropriate Visuals for Different Data Types; Creating Charts (Bar, Pie, Line, Histogram, Scatter Plot); Conditional Formatting for Quick Data Analysis
Break Week - No Classes
Mid-Cohort Break
Introduction to Data Visualization; Selecting Appropriate Visuals for Different Data Types; Creating Charts (Bar, Pie, Line, Histogram, Scatter Plot); Conditional Formatting for Quick Data Analysis
K-Means objective & k-means++, elbow method, DBSCAN (eps, min_samples, noise), Hierarchical clustering & dendrograms.
Conducting Exploratory Data Analysis (EDA) in Excel; Building Dashboards in Excel for Interactive Reporting; Excel Project: Dataset Selection, Data Cleaning, Transformation, Analysis, and Dashboard Creation
Mid-Cohort Break
Conducting Exploratory Data Analysis (EDA) in Excel; Building Dashboards in Excel for Interactive Reporting; Excel Project: Dataset Selection, Data Cleaning, Transformation, Analysis, and Dashboard Creation
Covariance matrix, eigenvalue decomposition, explained variance — PCA from scratch; t-SNE perplexity tuning; UMAP global structure. Module 2 Assessment & Project briefing.
Detailed session on Data Lakes with AWS S3 & Redshift
Detailed session on Self-Hosted n8n Operations
Data Analytics and Microsoft; Getting Started with Power BI; Getting Data in Power BI; Optimizing Performance; Resolving Data Errors; Lab: Preparing Data in Power BI Desktop
Detailed session on Support Vector Machines & Kernels
Tokenization; Text Preprocessing (Stop Word Removal, Stemming and Lemmatization); Text Representation (BoW, TF-IDF); Word Embeddings
Data Analytics and Microsoft; Getting Started with Power BI; Getting Data in Power BI; Optimizing Performance; Resolving Data Errors; Lab: Preparing Data in Power BI Desktop
Timestamp indexing, resampling, rolling windows, stationarity (ADF test), ACF/PACF, ARIMA & SARIMA modelling.
Detailed session on GCP BigQuery Fundamentals
Detailed session on Building Complex Enterprise Automations
Shaping the Data; Profiling the Data; Enhancing the Data Structure; Cleaning, Transforming, and Loading Data in Power BI; Lab: Loading Data in Power BI Desktop
Detailed session on Naive Bayes & Text Classification
Common NLP Tasks; Text Classification with Machine Learning Models
Shaping the Data; Profiling the Data; Enhancing the Data Structure; Cleaning, Transforming, and Loading Data in Power BI; Lab: Loading Data in Power BI Desktop
Prophet changepoints, holiday effects, uncertainty intervals; user-item matrices, cosine similarity, ALS matrix factorisation.
Detailed session on Star vs. Snowflake Schemas
Detailed session on Airtable Relational Databases
Introduction to Data Modeling; Working with Tables; Dimensions and Hierarchies; Lab: Creating Model Relationships, Configuring Tables and Column Properties, Creating Hierarchies; Introduction to DAX
Detailed session on K-Nearest Neighbors & Clustering Intro
Large Language Models; Foundational Models; Transformer Architecture (Encoder, Decoder, Self-Attention Mechanism)
Introduction to Data Modeling; Working with Tables; Dimensions and Hierarchies; Lab: Creating Model Relationships, Configuring Tables and Column Properties, Creating Hierarchies; Introduction to DAX
GridSearchCV vs RandomizedSearchCV vs Bayesian Optuna; from classical ML to transformers: attention, BERT, GPT, T5.
Detailed session on Data Modeling with dbt
Detailed session on Automated Executive Dashboards
Advanced DAX Concepts; Lab: Introduction to DAX (Calculated Tables, Calculated Columns, Measures); Lab: Advanced DAX (CALCULATE() Function, Time Intelligence Functions); Optimizing the Data Model for Performance
Detailed session on Gradient Boosting & XGBoost Mastery
Prompt Injection; Hallucination; GANs (Generator and Discriminator); Evaluation Metrics (ROUGE Score, BLEU, METEOR and Perplexity)
Advanced DAX Concepts; Lab: Introduction to DAX (Calculated Tables, Calculated Columns, Measures); Lab: Advanced DAX (CALCULATE() Function, Time Intelligence Functions); Optimizing the Data Model for Performance
Perceptron, backpropagation, self-attention mechanism, GPT decoder-only vs BERT bidirectional encoder, prompt engineering basics.
Detailed session on Hadoop Ecosystem & HDFS
Detailed session on Webhooks Integration Basics
Optimizing DirectQuery Models; Designing a Report; Enhancing the Report; Lab: Designing a Report in Power BI Desktop; Lab: Enhancing Reports (Sync Slicers, Drillthrough, Conditional Formatting, Bookmarks)
Detailed session on K-Means & Principal Component Analysis (PCA)
What is a Workflow?; Workflow vs AI Agent; LLM APIs; Guardrails; Prompt Engineering; Roles (User, Assistant, System); Structured Output with Pydantic Models
Optimizing DirectQuery Models; Designing a Report; Enhancing the Report; Lab: Designing a Report in Power BI Desktop; Lab: Enhancing Reports (Sync Slicers, Drillthrough, Conditional Formatting, Bookmarks)
Chains, prompt templates, memory types (buffer, summary, entity), multi-step prompts, chain-of-thought and ReAct patterns.
Detailed session on Apache Spark & PySpark Processing
Detailed session on Securing Connected Infrastructure
Creating Dashboards in Power BI; Publishing and Sharing Reports; Power BI Service Overview; Power BI Project: Real-World Dataset, Cleaning, Modelling, Analyzing Data; Designing Interactive Dashboard and Crafting Narrative
Detailed session on Anomaly Detection Systems
LLM APIs; Tool Calling; Memory; Context Engineering; Prompt Chaining, Parallelization and Routing
Creating Dashboards in Power BI; Publishing and Sharing Reports; Power BI Service Overview; Power BI Project: Real-World Dataset, Cleaning, Modelling, Analyzing Data; Designing Interactive Dashboard and Crafting Narrative
Document loaders, text splitters, FAISS & Chroma embeddings, custom tools, agent types — build an end-to-end RAG chatbot.
Detailed session on Kafka Architecture & Setup
Detailed session on Designing Conversational Chatbots
Overview of SQL as a Language; Common Use Cases of SQL; Importance of SQL in Data Querying; Introduction to DBMS; Understanding Relational Databases; Entity Relationship Diagrams (ERD); Setting Up PostgreSQL and pgAdmin
Detailed session on Forecasting with Time Series Data
AI Agents (with LangChain and LangGraph); LangChain Components; Tool Calling; Structured Output
Overview of SQL as a Language; Common Use Cases of SQL; Importance of SQL in Data Querying; Introduction to DBMS; Understanding Relational Databases; Entity Relationship Diagrams (ERD); Setting Up PostgreSQL and pgAdmin
Generator/discriminator minimax game, DCGAN, WGAN, StyleGAN; forward/reverse diffusion, U-Net, Stable Diffusion.
Detailed session on Real-Time Streaming with Spark
Detailed session on Support Ticketing Automation
Types of SQL Statements (DDL, DML, DCL, TCL); Querying Single and Multiple Tables; Selecting Specific Columns and Filtering with WHERE; Arithmetic Operators; Logical Operators (AND, OR, NOT); Comparison Operators (=, <, >, <=, >=, <>)
Detailed session on Building Collaborative Filtering Engines
LangGraph for Orchestration; Nodes, Edges and State; Conditional Edges; Reducers; Building Agents with LangGraph
Types of SQL Statements (DDL, DML, DCL, TCL); Querying Single and Multiple Tables; Selecting Specific Columns and Filtering with WHERE; Arithmetic Operators; Logical Operators (AND, OR, NOT); Comparison Operators (=, <, >, <=, >=, <>)
Streamlit/Flask LLM app deployment, API key management, bias in generative models, responsible AI. Module 3 Assessment & Project briefing.
Purpose of JOINs; Primary and Foreign Keys; Aliasing Tables and Columns; Types of JOINs (INNER, LEFT, RIGHT, FULL, SELF, CROSS); Practical JOIN Exercises with Real Datasets
Detailed session on Building REST APIs for Pipelines
Detailed session on Optimizing Marketing Automation
Purpose of JOINs; Primary and Foreign Keys; Aliasing Tables and Columns; Types of JOINs (INNER, LEFT, RIGHT, FULL, SELF, CROSS); Practical JOIN Exercises with Real Datasets
Detailed session on Hyperparameter Tuning with Optuna
Introduction to RAG (Retrieval-Augmented Generation); Why RAG; Understanding the RAG Pipeline
Code review session, debugging, README polish, GitHub portfolio curation, CV & LinkedIn optimisation.
Subqueries (Single-row, Multi-row, Correlated); Common Table Expressions (CTEs); Aggregate Functions (COUNT, SUM, AVG, MIN, MAX); GROUP BY and HAVING Clauses; Window Functions (ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG)
Detailed session on Webhooks & Automated Triggers
Detailed session on HR & Operations Transformation
Subqueries (Single-row, Multi-row, Correlated); Common Table Expressions (CTEs); Aggregate Functions (COUNT, SUM, AVG, MIN, MAX); GROUP BY and HAVING Clauses; Window Functions (ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG)
Detailed session on Machine Learning Architecture for AI
Building RAG System 1; Knowledge Source; Document Loading; Chunking; Embedding; Vector Databases; Similarity Search and Retrievers
Capstone demos, final assessment debrief, certificate award, alumni network onboarding, and career next steps.
Handling Missing Data in SQL; Standardizing and Normalizing Data; Removing Duplicates; Indexing for Faster Queries; Views for Organized Reporting; Stored Procedures and Functions
Detailed session on Data Privacy, GDPR & PII
Detailed session on Frameworks for AI Agents
Handling Missing Data in SQL; Standardizing and Normalizing Data; Removing Duplicates; Indexing for Faster Queries; Views for Organized Reporting; Stored Procedures and Functions
Detailed session on Introduction to Large Language Models
Building RAG System 2; Knowledge Source; Document Loading; Chunking; Embedding; Vector Databases; Similarity Search and Retrievers
SQL Project: Loading, Cleaning, and Organizing Data; Performing Complex Queries Including Joins; Aggregating and Analyzing Data to Derive Insights; Query Optimization Best Practices
Detailed session on Identity & Access Control Systems
Detailed session on Designing Autonomous Systems
SQL Project: Loading, Cleaning, and Organizing Data; Performing Complex Queries Including Joins; Aggregating and Analyzing Data to Derive Insights; Query Optimization Best Practices
Detailed session on Developing Apps with LangChain
AI Evaluation; Deployment
Advanced SQL: Recursive CTEs, Pivoting Data, Dynamic SQL; SQL Best Practices and Performance Tuning; Integrating SQL with Excel and Power BI Workflows; Data Pipeline Concepts
Detailed session on Infrastructure for Serving ML Models
Detailed session on Strategic Transformation Formulation
Advanced SQL: Recursive CTEs, Pivoting Data, Dynamic SQL; SQL Best Practices and Performance Tuning; Integrating SQL with Excel and Power BI Workflows; Data Pipeline Concepts
Detailed session on Deploying Generative AI Applications
Final SQL Project Presentations and Peer Review; Bootcamp Wrap-Up: Consolidating Excel, SQL, and Power BI Skills; Portfolio Guidance and Career Next Steps; Capstone Project Introduction and Planning
Detailed session on Final Capstone Pipeline Deployment
Detailed session on Final Capstone Presentation
Final SQL Project Presentations and Peer Review; Bootcamp Wrap-Up: Consolidating Excel, SQL, and Power BI Skills; Portfolio Guidance and Career Next Steps; Capstone Project Introduction and Planning
Detailed session on Capstone Finalization & Portfolio Review
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
Break Week - No Classes
Introduction to Data Visualization; Selecting Appropriate Visuals for Different Data Types; Creating Charts (Bar, Pie, Line, Histogram, Scatter Plot); Conditional Formatting for Quick Data Analysis
Conducting Exploratory Data Analysis (EDA) in Excel; Building Dashboards in Excel for Interactive Reporting; Excel Project: Dataset Selection, Data Cleaning, Transformation, Analysis, and Dashboard Creation
Data Analytics and Microsoft; Getting Started with Power BI; Getting Data in Power BI; Optimizing Performance; Resolving Data Errors; Lab: Preparing Data in Power BI Desktop
Shaping the Data; Profiling the Data; Enhancing the Data Structure; Cleaning, Transforming, and Loading Data in Power BI; Lab: Loading Data in Power BI Desktop
Introduction to Data Modeling; Working with Tables; Dimensions and Hierarchies; Lab: Creating Model Relationships, Configuring Tables and Column Properties, Creating Hierarchies; Introduction to DAX
Advanced DAX Concepts; Lab: Introduction to DAX (Calculated Tables, Calculated Columns, Measures); Lab: Advanced DAX (CALCULATE() Function, Time Intelligence Functions); Optimizing the Data Model for Performance
Optimizing DirectQuery Models; Designing a Report; Enhancing the Report; Lab: Designing a Report in Power BI Desktop; Lab: Enhancing Reports (Sync Slicers, Drillthrough, Conditional Formatting, Bookmarks)
Creating Dashboards in Power BI; Publishing and Sharing Reports; Power BI Service Overview; Power BI Project: Real-World Dataset, Cleaning, Modelling, Analyzing Data; Designing Interactive Dashboard and Crafting Narrative
Overview of SQL as a Language; Common Use Cases of SQL; Importance of SQL in Data Querying; Introduction to DBMS; Understanding Relational Databases; Entity Relationship Diagrams (ERD); Setting Up PostgreSQL and pgAdmin
Types of SQL Statements (DDL, DML, DCL, TCL); Querying Single and Multiple Tables; Selecting Specific Columns and Filtering with WHERE; Arithmetic Operators; Logical Operators (AND, OR, NOT); Comparison Operators (=, <, >, <=, >=, <>)
Purpose of JOINs; Primary and Foreign Keys; Aliasing Tables and Columns; Types of JOINs (INNER, LEFT, RIGHT, FULL, SELF, CROSS); Practical JOIN Exercises with Real Datasets
Subqueries (Single-row, Multi-row, Correlated); Common Table Expressions (CTEs); Aggregate Functions (COUNT, SUM, AVG, MIN, MAX); GROUP BY and HAVING Clauses; Window Functions (ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG)
Handling Missing Data in SQL; Standardizing and Normalizing Data; Removing Duplicates; Indexing for Faster Queries; Views for Organized Reporting; Stored Procedures and Functions
SQL Project: Loading, Cleaning, and Organizing Data; Performing Complex Queries Including Joins; Aggregating and Analyzing Data to Derive Insights; Query Optimization Best Practices
Advanced SQL: Recursive CTEs, Pivoting Data, Dynamic SQL; SQL Best Practices and Performance Tuning; Integrating SQL with Excel and Power BI Workflows; Data Pipeline Concepts
Final SQL Project Presentations and Peer Review; Bootcamp Wrap-Up: Consolidating Excel, SQL, and Power BI Skills; Portfolio Guidance and Career Next Steps; Capstone Project Introduction and Planning
Image Classification with CNN; Sequential Data with Recurrent Neural Networks; LSTM; GRU; Limitations of RNNs and LSTMs
Mid-Cohort Break
Mid-Cohort Break
Tokenization; Text Preprocessing (Stop Word Removal, Stemming and Lemmatization); Text Representation (BoW, TF-IDF); Word Embeddings
Common NLP Tasks; Text Classification with Machine Learning Models
Large Language Models; Foundational Models; Transformer Architecture (Encoder, Decoder, Self-Attention Mechanism)
Prompt Injection; Hallucination; GANs (Generator and Discriminator); Evaluation Metrics (ROUGE Score, BLEU, METEOR and Perplexity)
What is a Workflow?; Workflow vs AI Agent; LLM APIs; Guardrails; Prompt Engineering; Roles (User, Assistant, System); Structured Output with Pydantic Models
LLM APIs; Tool Calling; Memory; Context Engineering; Prompt Chaining, Parallelization and Routing
AI Agents (with LangChain and LangGraph); LangChain Components; Tool Calling; Structured Output
LangGraph for Orchestration; Nodes, Edges and State; Conditional Edges; Reducers; Building Agents with LangGraph
Introduction to RAG (Retrieval-Augmented Generation); Why RAG; Understanding the RAG Pipeline
Building RAG System 1; Knowledge Source; Document Loading; Chunking; Embedding; Vector Databases; Similarity Search and Retrievers
Building RAG System 2; Knowledge Source; Document Loading; Chunking; Embedding; Vector Databases; Similarity Search and Retrievers
AI Evaluation; Deployment
Detailed session on Conditional Routing & Logic
Break Week - No Classes
Detailed session on Self-Hosted n8n Operations
Detailed session on Building Complex Enterprise Automations
Detailed session on Airtable Relational Databases
Detailed session on Automated Executive Dashboards
Detailed session on Webhooks Integration Basics
Detailed session on Securing Connected Infrastructure
Detailed session on Designing Conversational Chatbots
Detailed session on Support Ticketing Automation
Detailed session on Optimizing Marketing Automation
Detailed session on HR & Operations Transformation
Detailed session on Frameworks for AI Agents
Detailed session on Designing Autonomous Systems
Detailed session on Strategic Transformation Formulation
Detailed session on Final Capstone Presentation
Detailed session on Random Forests & Ensemble Learning
Gaussian processes, acquisition functions, Optuna trials, AutoML with TPOT — tune XGBoost and compare.
Break Week - No Classes
K-Means objective & k-means++, elbow method, DBSCAN (eps, min_samples, noise), Hierarchical clustering & dendrograms.
Covariance matrix, eigenvalue decomposition, explained variance — PCA from scratch; t-SNE perplexity tuning; UMAP global structure. Module 2 Assessment & Project briefing.
Detailed session on Support Vector Machines & Kernels
Timestamp indexing, resampling, rolling windows, stationarity (ADF test), ACF/PACF, ARIMA & SARIMA modelling.
Detailed session on Naive Bayes & Text Classification
Prophet changepoints, holiday effects, uncertainty intervals; user-item matrices, cosine similarity, ALS matrix factorisation.
Detailed session on K-Nearest Neighbors & Clustering Intro
GridSearchCV vs RandomizedSearchCV vs Bayesian Optuna; from classical ML to transformers: attention, BERT, GPT, T5.
Detailed session on Gradient Boosting & XGBoost Mastery
Perceptron, backpropagation, self-attention mechanism, GPT decoder-only vs BERT bidirectional encoder, prompt engineering basics.
Detailed session on K-Means & Principal Component Analysis (PCA)
Chains, prompt templates, memory types (buffer, summary, entity), multi-step prompts, chain-of-thought and ReAct patterns.
Detailed session on Anomaly Detection Systems
Document loaders, text splitters, FAISS & Chroma embeddings, custom tools, agent types — build an end-to-end RAG chatbot.
Detailed session on Forecasting with Time Series Data
Generator/discriminator minimax game, DCGAN, WGAN, StyleGAN; forward/reverse diffusion, U-Net, Stable Diffusion.
Detailed session on Building Collaborative Filtering Engines
Streamlit/Flask LLM app deployment, API key management, bias in generative models, responsible AI. Module 3 Assessment & Project briefing.
Detailed session on Hyperparameter Tuning with Optuna
Code review session, debugging, README polish, GitHub portfolio curation, CV & LinkedIn optimisation.
Detailed session on Machine Learning Architecture for AI
Capstone demos, final assessment debrief, certificate award, alumni network onboarding, and career next steps.
Detailed session on Introduction to Large Language Models
Detailed session on Developing Apps with LangChain
Detailed session on Deploying Generative AI Applications
Detailed session on Capstone Finalization & Portfolio Review
Break Week - No Classes
Introduction to Data Visualization; Selecting Appropriate Visuals for Different Data Types; Creating Charts (Bar, Pie, Line, Histogram, Scatter Plot); Conditional Formatting for Quick Data Analysis
Conducting Exploratory Data Analysis (EDA) in Excel; Building Dashboards in Excel for Interactive Reporting; Excel Project: Dataset Selection, Data Cleaning, Transformation, Analysis, and Dashboard Creation
Data Analytics and Microsoft; Getting Started with Power BI; Getting Data in Power BI; Optimizing Performance; Resolving Data Errors; Lab: Preparing Data in Power BI Desktop
Shaping the Data; Profiling the Data; Enhancing the Data Structure; Cleaning, Transforming, and Loading Data in Power BI; Lab: Loading Data in Power BI Desktop
Introduction to Data Modeling; Working with Tables; Dimensions and Hierarchies; Lab: Creating Model Relationships, Configuring Tables and Column Properties, Creating Hierarchies; Introduction to DAX
Advanced DAX Concepts; Lab: Introduction to DAX (Calculated Tables, Calculated Columns, Measures); Lab: Advanced DAX (CALCULATE() Function, Time Intelligence Functions); Optimizing the Data Model for Performance
Optimizing DirectQuery Models; Designing a Report; Enhancing the Report; Lab: Designing a Report in Power BI Desktop; Lab: Enhancing Reports (Sync Slicers, Drillthrough, Conditional Formatting, Bookmarks)
Creating Dashboards in Power BI; Publishing and Sharing Reports; Power BI Service Overview; Power BI Project: Real-World Dataset, Cleaning, Modelling, Analyzing Data; Designing Interactive Dashboard and Crafting Narrative
Overview of SQL as a Language; Common Use Cases of SQL; Importance of SQL in Data Querying; Introduction to DBMS; Understanding Relational Databases; Entity Relationship Diagrams (ERD); Setting Up PostgreSQL and pgAdmin
Types of SQL Statements (DDL, DML, DCL, TCL); Querying Single and Multiple Tables; Selecting Specific Columns and Filtering with WHERE; Arithmetic Operators; Logical Operators (AND, OR, NOT); Comparison Operators (=, <, >, <=, >=, <>)
Purpose of JOINs; Primary and Foreign Keys; Aliasing Tables and Columns; Types of JOINs (INNER, LEFT, RIGHT, FULL, SELF, CROSS); Practical JOIN Exercises with Real Datasets
Subqueries (Single-row, Multi-row, Correlated); Common Table Expressions (CTEs); Aggregate Functions (COUNT, SUM, AVG, MIN, MAX); GROUP BY and HAVING Clauses; Window Functions (ROW_NUMBER, RANK, DENSE_RANK, LEAD, LAG)
Handling Missing Data in SQL; Standardizing and Normalizing Data; Removing Duplicates; Indexing for Faster Queries; Views for Organized Reporting; Stored Procedures and Functions
SQL Project: Loading, Cleaning, and Organizing Data; Performing Complex Queries Including Joins; Aggregating and Analyzing Data to Derive Insights; Query Optimization Best Practices
Advanced SQL: Recursive CTEs, Pivoting Data, Dynamic SQL; SQL Best Practices and Performance Tuning; Integrating SQL with Excel and Power BI Workflows; Data Pipeline Concepts
Final SQL Project Presentations and Peer Review; Bootcamp Wrap-Up: Consolidating Excel, SQL, and Power BI Skills; Portfolio Guidance and Career Next Steps; Capstone Project Introduction and Planning
Detailed session on Introduction to Apache Airflow
Break Week - No Classes
Detailed session on Data Lakes with AWS S3 & Redshift
Detailed session on GCP BigQuery Fundamentals
Detailed session on Star vs. Snowflake Schemas
Detailed session on Data Modeling with dbt
Detailed session on Hadoop Ecosystem & HDFS
Detailed session on Apache Spark & PySpark Processing
Detailed session on Kafka Architecture & Setup
Detailed session on Real-Time Streaming with Spark
Detailed session on Building REST APIs for Pipelines
Detailed session on Webhooks & Automated Triggers
Detailed session on Data Privacy, GDPR & PII
Detailed session on Identity & Access Control Systems
Detailed session on Infrastructure for Serving ML Models
Detailed session on Final Capstone Pipeline Deployment
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.
No upcoming schedules found for this course.