Lectures related to Excitonic Devices: Modeling and 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.

Introduction to Data Science

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

Data Science Visualization with Pandas

Covers data manipulation and exploration using Python with a focus on visualization techniques.

Semiconductor Devices II: Defects Engineering

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

Data Wrangling with Hive: Managing Big Data Efficiently

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

Semiconductor Devices II: Contact Resistance Modeling

Explores contact resistance modeling in semiconductor devices, focusing on gate voltage calculation and defect analysis.

MOSFET Basics: NMOS and PMOS Characteristics

Provides an overview of MOSFET operation, focusing on NMOS and PMOS characteristics, including current equations and channel modulation effects.

Common Source Amplifier Exercise

Covers the exercise on determining key parameters of a common source amplifier.

Data Science with Python: Numpy Basics

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

Building Tomorrow’s Electronics: From Atoms to Devices

Delves into the evolution of transistors, the impact of quantum effects on nano-devices, and the functionality of memristors.

Analog CMOS Integrated Circuits: Fundamentals

Covers the fundamentals of analog CMOS integrated circuits, emphasizing transistor-level design principles and the historical impact of CMOS technology.

Logic Systems: Karnaugh Maps and TTL Gates

Explores Karnaugh maps, TTL gates, analog aspects of digital logic, and prime implicants.

Data Science for Engineers: Part 2

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

Computer Architecture: Electronic Memory (Transistor-based)

Explains electronic memory in computer architecture using transistor-based circuits for data storage and retrieval.

Data Wrangling with Hadoop: Storage Formats and Hive

Explores data wrangling with Hadoop, emphasizing storage formats and Hive for big data processing.

3D Stone Scanning Session

Introduces a 'professional' 3D measurement system for stone analysis and feature extraction using stereo photogrammetry and structured light technologies.

Decision Tree Classification

Covers decision tree classification using KNIME Analytics Platform for data preprocessing and model creation.

Integrated Circuits: Evolution and Fabrication

Explores the evolution of integrated circuits, from transistors to CMOS technology, highlighting key historical milestones.

Neuromorphic Computing: Concepts and Hardware Implementations

Covers neuromorphic computing, challenges in ternary and binary computing, hardware simulations of the brain, and new materials for artificial brain cells.

Transistor MOS and CMOS Logic

Introduces MOSFET transistors and CMOS logic circuits, highlighting the impact of miniaturization on semiconductor technology.