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Related lectures (32)
Advanced Pandas Functions
Focuses on advanced pandas functions for data manipulation, exploration, and visualization with Python, emphasizing the importance of understanding and preparing data.
Introduction to Data Science
Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Data Science: Python for Engineers - Part II
Explores data wrangling, numerical data handling, and scientific visualization using Python for engineers.
Introduction to Renku
Introduces Renku, a platform for collaborative data science, emphasizing reproducibility, shareability, reusability, and security.
Regression Models: Performance and Evaluation
Explores regression model performance, learning errors, and building regression trees using the CART algorithm.
Collaborative Data Science: Tools and Git Workflow
Explores tools like Git and Docker for collaborative data science projects.
Data Science Visualization with Pandas
Covers data manipulation and exploration using Python with a focus on visualization techniques.
Big Data Ecosystems: Technologies and Challenges
Covers the fundamentals of big data ecosystems, focusing on technologies, challenges, and practical exercises with Hadoop's HDFS.
Introduction to Continuum Mechanics
Covers scaling, mathematical modeling, tensor notation, and Python exercises in Jupyter notebooks.
Advanced Spark Optimization
Delves into advanced Spark optimization techniques, emphasizing data partitioning, shuffle operations, and memory management.