AI ML Step by Step Using C#, Python, Azure and OpenAI
Live Training + Recordings
What you'll learn :-
Are you a C# Developer ? who is looking to make career in AI ML then you have reached the right place.Many AI ML courses out there use Python and other LLM's to do AI ML. But when it comes to Microsoft developers they would like to leverage C# , ML.NET , Azure AI , Azure Open AI. This course exactly does that kind of Justice for C# Developers.
*Special discount for Early Bird and Questpond members (Actual Cost: ₹50K/$590).
Training Content
4
Modules
67
Lessons
50
Hands-on Labs
40+
Hours
/ 02 Curriculum
01 26 lessons
What is AI and ML?
How Humans Learn — Features, Labels & Alphabet Image Data Format
Features, Labels, Algorithm, Training, Model — the FLATM model
Understanding FLATM using a simple Excel sheet
Algorithm (Formula) vs Model
Defining Regression
Simplest ML.NET regression code — MLContext & MKL components
Model is a Mathematical Formula
Inference vs Training
Road Map for AI ML
The Psychology of ML.NET Code Pipeline
Multi-Features Example and Algorithm Confusion
OLS (Ordinary Least Squares) and SDCA (Stochastic Dual Coordinate Ascent)
R Square and RMSE (Root Mean Squared)
AUTOML
Everything is a VECTOR
OLS with Polynomial Data
AutoML and Cosine and Euclidean
Feature Engineering
Linear, Non-Linear and Seasonal
Supervised Learning and Unsupervised Learning
Clustering Algorithms and KMeans
Vector, Tokens, Encoding, Embedding, Transformer, BERT and GPT
MLP Encodings — One-Hot, BOW, TF-IDF, Word & Transformer Embeddings
Prompt Engineering (Personal, Task, Context, Constraints & Format)
Data Quality — Descriptive Statistics, Outliers, Min/Max, Median, Mode, Stdev, Skewness, Kurtosis, Quartiles
Python Basics — Comments, Indents and Blocks
Variable Declaration and Dynamism
Simple For Loops and Functions
Arrays in Python
Writing Classes, Functions and Creating Objects
Packages, Modules, Classes and OOP
Numpy Fundamentals
Pandas Fundamentals
AUTOML
Load Huge File and Check AUTOML Suggestions and Accuracy
Saving Model and Retraining — SDCA and Online Gradient Descent
Binary / Logistic Regression
Multi-Class Classification
Simple Clustering Example using KMeans
Understanding One-Hot Encoding
Simple Example of BOW
Simple Example of TF-IDF
Word Embedding using GloVe50D — Cosine and Euclidean Similarity
Simple BERT Example
GPT Example with Offline Encoding
ChatGPT Demonstrating Transformer
Simple RAG Demonstration
Chunking — Fixed, Recursive, Semantic, Hierarchical, Topic, Modality, Agentic
Prompt Basics using ChatGPT
PyTorch Fundamentals
Creating a Model using PyTorch — Simple Linear Regression
Linear Regression Deep Dive (PyTorch)
Consuming ONNX File
Understanding TensorFlow
Creating Azure AI Workspace — Linear Regression with AUTOML
Creating a Model using Azure AI Designer (Inference Pipeline)
Debugging AI Issues in Azure
Advanced Debugging AI Issues in Azure
Azure Foundry Demo — Agents, Evals and MCP (Model Context Protocol)
Agentic AI with Semantic Kernel (C#)
Agentic AI with LangChain and LangGraph (Python)
N8N Demo — Triggers, Set Fields, OpenAI and Webhooks
Data Quality
Microsoft Extension.AI
Generative AI
🚀
Capstone Projects
Dotnet Interview Mate & Nifty Prediction
World-class training and development programs developed by top teachers
Whats Included
- World-class training teacher
- Bench has zero learning curve
- We handle the rest.