Data Science Festival Courses

Graphs Are Everywhere - Understanding Graph Databases and Social Graphs

Explore graph databases and their applications in social networks, analytics, and decision-making. Learn about their scalability, performance, and advantages over traditional databases for interconnected data.

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

Your First Data Science Project: Planning for Success

Learn effective project management techniques for data science, covering agile and waterfall methodologies, autoML, model monitoring, and data drift to ensure successful implementation of data-driven initiatives.

• YouTube
• 1 hour 3 minutes
• Self-Paced
• Free Video

Using the FLiPN Stack for Edge AI

Explore the FLiPN stack for building fast IoT and AI applications. Learn how Apache Flink, NiFi, and Pulsar combine to create scalable streaming solutions for edge computing and rapid data ingestion.

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

The Dangers of Dirty Data: Ensuring Accuracy in Classification

Explore the consequences of dirty data and learn practical techniques for ensuring data accuracy and maintenance in this insightful talk by Susan Walsh.

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

Quality Assurance and Machine Learning Model Validation

Explore key steps in machine learning model validation and quality assurance, from bias detection to data leak prevention, enhancing your MLOps process.

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

Graph Machine Learning: Enhancing ML with Network Graphs and Embeddings

Explore graph-based machine learning techniques to enhance data analysis and uncover hidden relationships in your datasets. Learn to leverage network graphs for improved model performance.

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

How to Deploy Machine Learning Models in Production

Learn to train, deploy, and maintain machine learning models in production environments, covering real-time decision-making and scalable frameworks for experimentation and deployment.

• YouTube
• 1 hour 1 minute
• Self-Paced
• Free Video

Feature Selection for Machine Learning

Explore feature selection methods for machine learning, including filter, wrapper, and embedded approaches. Learn to choose the most predictive variables for production-ready models.

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

Data Ethics - Mitigating Bias in Algorithms

Explore strategies for mitigating bias in AI algorithms, addressing a critical challenge faced by tech companies to build consumer trust and ensure ethical AI development.

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

Data Storytelling and Visualization

Learn effective techniques for communicating data-driven concepts through storytelling and visualization, applicable to both expert and non-expert audiences.

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

Data Preprocessing and Feature Engineering for Machine Learning

Master data preprocessing and feature engineering techniques for effective machine learning. Explore imputation, encoding, transformations, and more to maximize value from your data and improve model performance.

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

Bayesian Machine Learning - Benefits, Drawbacks, and Practical Applications

Explore Bayesian machine learning's benefits and drawbacks, focusing on model uncertainty and prior knowledge injection. Learn practical applications from Wise's Head of AI.

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

Advanced Python Libraries for Data Science

Explore advanced Python libraries for data science, focusing on scikit-learn, TensorFlow, and PyTorch Geometric. Learn implementation, methodologies, and practical applications through code exercises.

• YouTube
• 1 hour 45 minutes
• Self-Paced
• Free Video

Top 4 Python Libraries for Data Science

Explore four essential Python libraries for data science: NumPy, Pandas, Matplotlib, and Seaborn. Learn their key benefits and practical applications in fundamental data science concepts.

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

Python 101 - Introduction to Python for Data Science

Learn Python basics for data science: explore versatile programming tools, efficient data computation, and knowledge extraction techniques.

• YouTube
• 1 hour 11 minutes
• Self-Paced
• Free Video