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Courses > Advanced AI & ML for Software Developers & Tech Professionals – 1 to 1

Advanced AI & ML for Software Developers & Tech Professionals – 1 to 1

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Last Updated: Sep 02, 2025

Tags: AI

About Course

This 2-week intensive program is designed for developers, data analysts, and technology professionals who already have a basic understanding of Python and machine learning. The course focuses on building production-ready AI and ML systems, mastering modern architectures, and applying advanced techniques in real-world projects. Participants will learn to design scalable ML pipelines, optimize and interpret models, implement deep learning and NLP solutions, and integrate AI into production using MLOps best practices. The program is highly practical, combining lectures with hands-on exercises, capstone projects, and access to reusable code templates.

Design scalable, production-ready ML pipelines with proper monitoring.
Implement advanced ensemble learning techniques such as boosting, bagging, and stacking.
Apply model interpretability tools like SHAP and LIME to explain predictions.
Optimize models using hyperparameter tuning frameworks such as Optuna and Hyperopt.
Work with unsupervised learning techniques for clustering and anomaly detection.
Build forecasting models for finance, sales, and operational planning.
Develop deep learning models with CNNs, RNNs, and Transformers.
Fine-tune large language models (BERT, GPT) for domain-specific applications.
Deploy AI solutions using MLOps tools like MLflow, DVC, and Kubeflow.
Build generative AI applications for text, images, and code.

+91 96452 47165

About Course

What Will You Learn?

Course Content

Day 1

ML System Design & Architecture

Model Deployment Strategies

Hands-on: Design a Scalable ML Pipeline Blueprint

Day 2

Ensemble Learning Techniques

Model Interpretability Tools

Hands-on: Build & Interpret an XGBoost Model on a Real Dataset

Day 3

Model Optimization & Hyperparameter Tuning

Cross-Validation & Evaluation Techniques

Hands-on: Tune and Evaluate a LightGBM Model

Day 4

Unsupervised Learning & Anomaly Detection

Dimensionality Reduction in Real Use Cases

Hands-on: Detect Anomalies in eCommerce Transactions

Day 5

Time-Series Forecasting & ML in Finance

ML for Predictive Analytics

Hands-on: Build a Forecasting Model Using Facebook Prophet

Day 6

Neural Networks Refresher & Architectures

Regularization, Dropout & BatchNorm

Hands-on: Build a Custom Image Classifier Using CNN (Keras/PyTorch)

Day 7

Transformers & NLP Models

LLMs in Practice

Hands-on: Fine-Tune a BERT Model for Product Review Sentiment Analysis

Day 8

AI in Production: MLOps Tools & Workflow

Model Registry & Lifecycle Management

Hands-on: Track and Register a Model Using MLflow

Day 9

Generative AI Applications

Prompt Engineering + Fine-tuning

Hands-on: Build a Chatbot Using Open Source LLM + Your Dataset

Day 10

Capstone Day: AI for Your Domain

Presentation + Model Deployment Tips

Bonus: Access to Model Zoo + Case Study Library

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