Digital Humanities: Interdisciplinary Approach to Data Science

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Data Science for Engineers: Part 2

Explores data manipulation, exploration, and visualization in data science projects using Python.

Data Science: Python for Engineers - Part II

Explores data wrangling, numerical data handling, and scientific visualization using Python for engineers.

Data Wrangling with Hive: Managing Big Data Efficiently

Covers data wrangling techniques using Apache Hive for efficient big data management.

Scopes and Lambdas: Data Science with Python

Covers scopes, lambdas, and pandas in data science with Python, including nested declarations, scoping, assignments, and pandas manipulation.

General Introduction to Data Science

Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.

Introduction: What do we mean by Data Science?

Introduces the team, provides a crash course on Python, and explores the journey into Data Science and the importance of refining data.

Introduction to Data Science

Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.

Shedding light on lives with logs

Explores using log data to understand human behaviors, focusing on food consumption and social interactions.

Data, big data, clouds and IoT

Explores data representation, databases, cloud computing, and challenges in the cloud environment.

Data Science Engineering: A Cognitive Science Perspective

Delves into the importance of understanding thought processes in data science tasks.