Lectures related to Wind Power Production Analysis

Data Wrangling with Hive: Managing Big Data Efficiently

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

Python Lists: Manipulation and Comprehension

Covers Python list manipulation and comprehension, emphasizing memory representation and mutability.

Python: Dictionaries and Tuples

Explores dictionaries, tuples, mutable objects, and variable-length arguments in Python.

Introduction to NumPy and Matplotlib for Scientific Computing

Introduces NumPy and Matplotlib, essential tools for scientific computing and data visualization in Python.

Model Representation: Structures and Functions

Covers the representation of mathematical models, functions, and data structures in information systems.

Python Programming: Data Structures and Functions

Covers advanced Python programming concepts, including data structures and functions.

Python Programming: Lists and Functions Overview

Introduces Python programming concepts, focusing on lists, functions, and their applications in problem-solving.

Data Modeling: Concepts and Applications

Introduces data modeling concepts, SQL usage, and Pandas library applications for efficient data processing.

Image Processing Techniques: Seam Carving and Pixel Manipulation

Discusses image processing techniques, focusing on seam carving and pixel manipulation in Python programming.

Functions and Lists: Complements and Manipulation

Explores functions' complements, parameter order, and list manipulation, including counting occurrences and solving the '100 prisoners problem'.

Python Programming: Dictionaries and Classes

Introduces Python programming concepts, focusing on dictionaries and classes, including their definitions, usage, and practical examples.

File Management and Exception Handling in Python

Focuses on file management and exception handling in Python programming.

Data Structures: Tuples, Sets, Dictionaries

Explores tuples, sets, and dictionaries in Python, covering immutability, uniqueness, and key-value pairs.

Data Science with Python

Covers Python basics, Pandas, data manipulation, visualization, and machine learning.

Introduction to Jupyter Exercises

Introduces Jupyter exercises on Differential Privacy, covering random generators, understanding data intrusion impact, and practical applications.

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.

Data Structures: Tuples, Lists, Sets, Dicts

Introduces data structures like tuples, lists, sets, and dicts in Python, covering their definition, manipulation, and iteration.

Dataclasses: Modeling and Classes

Introduces dataclasses for modeling complex structures and defining custom variable types.

Introduction to C Programming

Introduces fundamental C programming concepts, covering variables, control structures, functions, and pointers, with practical examples and exercises.

Data, big data, clouds and IoT

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