What you'll learn
What Quantum Computing is as a field
Deep Research insights on application of Quantum Computing
How to think Critically of Data Science using Quantum computing
Build a Quantum Computing backed Machine Learning Model
Requirements
Basic Python Understanding
Description
Quantum computing is a new and rapidly developing field with the potential to revolutionize many industries, including data science. Quantum computers can perform certain types of calculations exponentially faster than classical computers, making them ideal for solving complex data science problems that are currently intractable.This course is perfect for anyone who wants to learn about quantum computing and how to use it to solve real-world data science problems. Whether you're a data scientist, a software engineer, or a student, this course will give you the ideas you need to try to work in the emerging field of quantum computing.There is no such thing as perfection in any field but this course will give you an idea of how to symbolize technological curiosity with implementation.Note this is a course that will help you understand how to use data science with quantum computing while highlighting the basics of it and not an advanced quantum computing course.In this course you will learn:How to use quantum computing to solve real-world data science problemsHow to use quantum algorithms with PythonPopular quantum algorithms for data science tasks such as machine learning.The basics of quantum mechanics and quantum computing.
Overview
Section 1: Introduction
Lecture 1 Introduction
Lecture 2 What is Quantum Computing?
Lecture 3 How is Quantum Computing Done?
Section 2: Applications of Quantum Computing in Data Science
Lecture 4 Section Introduction
Lecture 5 Quantum Machine Learning
Lecture 6 Experimental Simulations Using Quantum Computing
Lecture 7 Cyber Security Applications with Quantum computing
Lecture 8 Agriculture Growth with Quantum Computing & Data Analytics
Lecture 9 Supply chain efficiency using Quantum computing applications
Lecture 10 Stock trading effectiveness with Quantum based predictive modeling
Section 3: Industrial Applications of Quantum Computing with Data Science
Lecture 11 Section Introduction
Lecture 12 Example use cases of Agriculture Growth with Quantum Computing & Data Analytics
Lecture 13 Examples of Manufacturing Optimization with Quantum Computing data analytics
Lecture 14 Examples of Stock trading effectiveness with Quantum based predictive modeling
Lecture 15 Examples of Supply chain efficiency using Quantum computing applications
Section 4: Conclusion of Quantum Computing with Data Science
Lecture 16 Section Introduction
Lecture 17 Can Quantum Computing be used in developing economies for business applications?
Lecture 18 How can small companies implement quantum computing with data analytics
Lecture 19 Developing Economies that have Invested in Quantum Computing Applications
Lecture 20 Challenges of Quantum Computing applications in Industrial context
Section 5: Machine Learning using Quantum computing with Python Lab
Lecture 21 Quantum Machine Learning with Python on Anaconda cloud
Beginners in Python,Beginners in Data Science

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