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Python/NumPy Primer

Introduces Python basics and NumPy for scientific computing, covering data types, functions, arrays, indexing, and common operations.

Excitonic Devices: Modeling and Applications

Covers excitonic device modeling and exciton control using 2D materials.

Introduction to R Programming for Genetics & Genomics

Introduces a course on Genetics & Genomics, focusing on R programming with interactive exercises.

Data Science with Python: Modules and Numpy

Introduces Python modules and NumPy for efficient array operations and linear algebra in data science.

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.

NumPy: Array Manipulation and Broadcasting

Covers array creation, indexing, manipulation, and broadcasting using NumPy in Python.

Elements of Computational Complexity

Introduces computational complexity, decision problems, quantum complexity, and probabilistic algorithms, including NP-hard and NP-complete problems.

Python Recap: Modules and Objects

Covers Python modules, objects, and data containers like lists and NumPy arrays.

Semiconductor Devices II: Defects Engineering

Covers the analysis of measurements and defects engineering in semiconductor devices, including density of states and defect probing.

Complex Systems: Critical Phenomena

Explores critical phenomena in complex systems, including stochastic objects, percolation, and combinatorial optimization.

Cryptanalysis: Public-Key & The Power of Interaction

Explores cryptanalysis in public-key systems and the power of interaction in interactive proofs, covering CO-NP, NP classes, P vs. NP, and more.

Introduction to Vector in C++

Introduces the fundamentals of vectors in C++, covering initialization, direct access, range-for loop, and specific functions.

Density Operator Formalism

Covers the density operator formalism, polynomial time, NP problems, BPP, QMA, and probabilistic algorithms.

Complexity Classes: P and NP

Explores complexity classes P and NP, highlighting solvable and verifiable problems, including NP-complete challenges.

Data Wrangling with Hive: Managing Big Data Efficiently

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

Neurophysiological Data Analysis

Explores neurophysiological data analysis, covering AP identification, firing rates, subthreshold activity, FFT spectral analysis, and event-triggered analysis using MATLAB.

Theory of Computability: Solvability and Complexity

Explores the theory of computability, decision problems, complexity classes, and the 'P vs. NP' conundrum.

Data Science with Python: Numpy Basics Log in to Mediaspace to watch this video

Introduces the basics of Numpy, a numerical computing library in Python, covering advantages, memory layout, operations, and linear algebra functions.

Numpy Tutorial Log in to Mediaspace to watch this video

Covers the basics of Numpy, including importing the library, creating arrays, and performing linear algebra operations.

NumPy Arrays and Graphical Representations: Introduction Log in to Mediaspace to watch this video

Covers NumPy arrays and their graphical representations using Matplotlib, focusing on array creation, manipulation, and visualization techniques.