Here I would provide some information and list of my completed and current working courses on Coursera platform. I will classify it by topic and will give misc to general knowledge courses that I took to expand my knowledge. links we take you to my certificate or course page if not completed

*On going*

*On going*

- Deep Learning in Computer Vision
- The Introduction to Quantum Computing
- Foundations of Data Science: K-Means Clustering in Python
- Exploring Quantum Physics

*Completed*

*Completed*

*Physics and Mathematics*

Understanding Einstein: The Special Theory of Relativity

Introduction to Ordinary Differential Equations

Fundamentals of particle accelerator technology

Medical Applications of Particle Accelerators

Intro to Acoustics (Part 1)

Introduction to Acoustics (Part 2)

Game Theory

Archaeoastronomy

Journey of the Universe: The Unfolding of Life

AstroTech: The Science and Technology behind Astronomical Discovery

Introduction to Thermodynamics: Transferring Energy from Here to There

From the Big Bang to Dark Energy

The Finite Element Method for Problems in Physics

Origins – Formation of the Universe, Solar System, Earth and Life

Quantum Optics 1 : Single Photons

Quantum Optics 2 – Two photons and more

Particle Physics: an Introduction

Statistical Molecular Thermodynamics

Fundamentals of Fluid Power

Matrix Factorization and Advanced Techniques

Renewable Energy and Green Building Entrepreneurship

Introduction into General Theory of Relativity

Addressing Large Hadron Collider Challenges by Machine Learning

Materials Science: 10 Things Every Engineer Should Know

Welcome to Game Theory

Big History: Connecting Knowledge

Astro 101: Black Holes

Nuclear Reactor Physics Basics

Game Theory II: Advanced Applications

Fibonacci Numbers and the Golden Ratio

Differential Equations for Engineers

Astrobiology and the Search for Extraterrestrial Life

Introduction to Molecular Spectroscopy

Electrodynamics: In-depth Solutions for Maxwell’s Equations

Factorial and Fractional Factorial Designs

*Data science*

Python for Everybody (Specialization)

Deep Learning (Specialization)

Data Science: Foundations using R (Specialization)

TensorFlow in Practice (Specialization)

AI for Medicine (Specialization)

Machine Learning (Specialization)

Mathematics for Machine Learning (Specialization)

Introduction to Data Science (Specialization)

Applied Data Science (Specialization)

TensorFlow: Data and Deployment (Specialization)

Getting Started with AWS Machine Learning

Introduction to Deep Learning & Neural Networks with Keras

Deep Neural Networks with PyTorch

Introduction to Applied Machine Learning

Fundamentals of Scalable Data Science

Big Data Integration and Processing

Device-based Models with TensorFlow Lite

Convolutional Neural Networks in TensorFlow

Launching into Machine Learning

How Google does Machine Learning

Sequences, Time Series and Prediction

Natural Language Processing in TensorFlow

Capstone: Retrieving, Processing, and Visualizing Data with Python

Programming for Everybody (Getting Started with Python)

Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization

Neural Networks and Deep Learning

Structuring Machine Learning Projects

Project: Multiple Linear Regression with scikit-learn

Project: Predicting House Prices with Regression using TensorFlow

Machine Learning With Big Data

AI Workflow: Enterprise Model Deployment

AI Workflow: Data Analysis and Hypothesis Testing

Mathematics for Machine Learning: Multivariate Calculus

Applied Machine Learning in Python

Mathematics for Machine Learning: Linear Algebra

Machine Learning: Clustering & Retrieval

Machine Learning: Classification

Machine Learning Foundations: A Case Study Approach

Neural Networks for Machine Learning

Bayesian Statistics: From Concept to Data Analysis

Mathematics for Machine Learning: PCA

Bayesian Methods for Machine Learning

Introduction to Recommender Systems: Non-Personalized and Content-Based

Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning

Using Python to Access Web Data

Recommender Systems: Evaluation and Metrics

Nearest Neighbor Collaborative Filtering

Introduction to Data Science in Python

Fundamentals of Machine Learning in Finance

Practical Reinforcement Learning

Guided Tour of Machine Learning in Finance

Browser-based Models with TensorFlow.js

Big Data Integration and Processing

AI Workflow: Enterprise Model Deployment

*Technology and Computer science*

Genome Assembly Programming Challenge

G Suite Security

G Suite Mail Management

Cyber Threat Intelligence

Blockchain for the decision maker

Cybersecurity for Identity Protection

Blockchain 360: A State of the Art for Professionals

Image and Video Processing: From Mars to Hollywood with a Stop at the Hospital

Introduction to Self-Driving Cars

State Estimation and Localization for Self-Driving Cars

Machine Learning With Big Data

Motion Planning for Self-Driving Cars

Visual Perception for Self-Driving Cars

*Misc*

Epidemiology in Public Health Practice (Specialization)

COVID-19: What You Need to Know (CME Eligible)

An Introduction to Consumer Neuroscience & Neuromarketing

Learning How to Learn: Powerful mental tools to help you master tough subjects

Fundamental Neuroscience for Neuroimaging

Philosophy, Science and Religion: Science and Philosophy

Meditation: A way to achieve your goals in your life

Mindshift: Break Through Obstacles to Learning and Discover Your Hidden Potential

International Travel Preparation, Safety, & Wellness

Learning How To Learn for Youth

An Introduction to American Law

Introduction to International Criminal Law

Introduction to Personal Branding

Emotions: a Philosophical Introduction

Intellectual Humility: Science

Introduction to Ancient Egypt and Its Civilization

Politics and Economics of International Energy

Philosophy and the Sciences: Introduction to the Philosophy of Physical Sciences

The Effect of Fires on People, Property and the Environment

intro to acoustics (part 1) Coursera quiz solution

Quiz 4 Question 6 Please Give me an answer to this Question only one question I can’t solve,

Let us assume that a wave propagates in the direction perpendicular to the flat surface of discontinuity. When the characteristic impedance of the medium of medium 0 (where the incident and reflected wave exists) is much larger than medium 1 (where the transmitted wave exists.), how do the pressure and intensity reflection and transmission coefficient behave? Choose all true statements.

Thank You,