MLCon | Machine Learning Conference Courses

The Untapped Potential of Audio ML Projects - Exploring Vocal Health Analysis

Explore the intersection of audio and machine learning, focusing on vocal health analysis and sound classification. Discover innovative applications and future potential in this emerging field.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

Prompt Engineering Best Practices for Productive Customer Interactions

Explore effective prompt engineering strategies for natural language customer interfaces, focusing on RAG techniques to navigate diverse company content and address customer queries seamlessly.

• YouTube
• 50 minutes
• Self-Paced
• Free Video

Beyond 2026 - The Role of AI-Generated Content in Machine Learning

Explore the impact of AI-generated content on machine learning, addressing bias challenges and strategies for the future of ML in light of evolving regulations and technological advancements.

• YouTube
• 46 minutes
• Self-Paced
• Free Video

AI is MagIA: Explaining AI Concepts with Card Tricks

Unravel AI mysteries through captivating card tricks. Explore data domains, GANs, biased opinions, and transfer learning in this unique blend of magic and technology. Entertaining and informative for all ages.

• YouTube
• 44 minutes
• Self-Paced
• Free Video

Why Security Is Important in ML and How To Secure Your ML-based Solutions

Explore security risks in AI/ML adoption, focusing on secure coding practices in Python. Learn techniques to improve code hygiene and protect against vulnerabilities in ML-based solutions.

• YouTube
• 55 minutes
• Self-Paced
• Conference Talk

Using A.I to Make Recommendations for Career Progression

Explore AI-driven career recommendations using multivariate matching algorithms. Learn how to identify suitable careers, quantify specialization, and gain insights into career progression paths beyond your current field.

• YouTube
• 28 minutes
• Self-Paced
• Conference Talk

Kotlin for Machine Learning

Explore Kotlin's potential in machine learning projects, from data cleaning to model deployment. Learn about Kotlin tools for data science, including Jupyter notebooks, visualizations, and dataframes.

• YouTube
• 48 minutes
• Self-Paced
• Conference Talk

Honey, I Shrunk the TinyML

Explore TinyML: train, convert, and run machine learning models on microcontrollers. Learn quantization, pruning techniques, and step-by-step integration for embedded AI applications.

• YouTube
• 49 minutes
• Self-Paced
• Conference Talk

Using Predictive Analytics and Machine Learning

Explore predictive analytics and machine learning applications from NASA to Hollywood, focusing on critical decisions, risk management, and innovative solutions in complex systems.

• YouTube
• 30 minutes
• Self-Paced
• Conference Talk

An Introduction to Natural Language Generation

Explore natural language generation through real-world examples, deep learning techniques, and transformer models. Learn about word embeddings, BERT, GPT, and practical applications in various domains.

• YouTube
• 49 minutes
• Self-Paced
• Conference Talk

MLOps - Automated Machine Learning Made Easy

Explore AI and ML optimization techniques to enhance business outcomes through data understanding and model improvement.

• YouTube
• 45 minutes
• Self-Paced
• Conference Talk

Language - The Next Stronghold to Be Taken by AI

Explore AI's impact on language, from recent breakthroughs to future possibilities, covering computer vision, natural language understanding, and feature learning.

• YouTube
• 39 minutes
• Self-Paced
• Conference Talk

Language - The Next Stronghold to Be Taken by AI

Explore recent AI breakthroughs and discover why natural language understanding is poised to be the next major frontier in artificial intelligence.

• YouTube
• 44 minutes
• Self-Paced
• Conference Talk

From NASA to Hollywood - Using Predictive Analytics and Machine Learning

Explore predictive analytics and machine learning applications in NASA spaceflight systems and Hollywood movie risk assessment, covering parametric and non-parametric models for high-risk, low-instance systems.

• YouTube
• 30 minutes
• Self-Paced
• Conference Talk

First Steps to Interpretable Machine Learning

Explore interpretable machine learning using SHAP values to understand model predictions and feature importance, based on a real data science project with practical insights.

• YouTube
• 21 minutes
• Self-Paced
• Conference Talk