Machine Learning & AI (Python, Ruby

Harness the power of Python and Ruby on Rails to build intelligent, data-driven applications.

Duration

2 Days

Language

English

Delivery Mode

Online/Hybrid/Face-to-Face

Course Overview

This comprehensive program is designed to equip participants with the essential skills to navigate the evolving landscape of Artificial Intelligence and Machine Learning. By combining the analytical dominance of Python with the rapid web development capabilities of Ruby on Rails, the course offers a unique perspective on building and deploying smart applications. From data preprocessing and algorithm selection to real-world project deployment, students will gain the expertise needed to transform raw data into actionable insights and sophisticated AI features.

Learning Objectives

Analyze and apply fundamental machine learning paradigms, including supervised, unsupervised, and reinforcement learning.
Develop high-level proficiency in Python libraries such as NumPy, Pandas, and Scikit-learn for data manipulation and model building.
Integrate AI-powered functionalities into web applications using the Ruby on Rails framework.
Execute data preprocessing and feature engineering techniques to optimize the performance of predictive models.
Evaluate model accuracy through rigorous testing, hyperparameter tuning, and cross-validation metrics.
Design and deploy end-to-end AI solutions that solve complex real-world problems and enhance organizational decision-making.

Course Outline

Day 01

Foundations of AI & ML: Core concepts, types of learning, and an introduction to the mathematical theory behind algorithms.
Python for Data Science: In-depth syntax training, data structure management, and leveraging specialized ML libraries.
Intelligent Web Frameworks: Utilizing Ruby on Rails to create the architecture for AI-driven web platforms.
Predictive Modeling & Algorithms: Deep dives into regression, decision trees, clustering, and neural network architectures.
Advanced AI Domains: Exploring Natural Language Processing (NLP), Computer Vision, and the logic of Expert Systems.
Lifecycle & Deployment: From raw data cleaning and model training to final evaluation and production deployment.

Certification

OrientMCT Certified

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