Top Free Data Structures And Algorithms Course With Certificate
Introduction to Algorithm Analysis [For Absolute Beginners]
About The Course:
This course will provide a very basic knowledge of Algorithm Analysis. This course is for anyone who has heard the word algorithm and has no idea about it. This course is for absolute beginners.
Introduction to Algorithms
Algorithms ( Flowcharts & Pseudacodes)
Algorithm Analysis – Part 1
Algorithm Analysis – Part 2 [Theoretical Analysis & Big O Notation ]12:53
Algorithm Analysis – Part 3 Big O Arithmetic
Big O, Big Omega, Big Theta
Two-Sum, Three Sum Algorithm Analysis
QuickFind – Dynamic Connectivity
Selection Sort
Artificial Intelligence Algorithms Models and Limitations
About The Course:
We live in an age increasingly dominated by algorithms. As machine learning models begin making important decisions based on massive datasets, we need to be aware of their limitations in the real world. Whether it’s making loan decisions or re-routing traffic, machine learning models need to accurately reflect our shared values. In this course, we will explore the rise of algorithms, from the most basic to the fully-autonomous, and discuss how to make them more ethically sound.
SKILLS YOU WILL GAIN
Understanding of algorithms
Familiarity with predictive models
Overview of ethics considerations
Machine Learning Algorithms: Supervised Learning Tip to Tail
About The Course:
This course takes you from understanding the fundamentals of a machine learning project. Learners will understand and implement supervised learning techniques on real case studies to analyze business case scenarios where decision trees, k-nearest neighbors, and support vector machines are optimally used. Learners will also gain skills to contrast the practical consequences of different data preparation steps and describe common production issues in applied ML.
What you will learn from this course
Classification using Decision Trees and k-NN
Functions for Fun and Profit
Regression for Classification: Support Vector Machines
Contrasting Models
Machine Learning: Algorithms in the Real World Specialization
About the Course:
Machine Learning Real World Applications. Master techniques for implementing a machine learning project.
WHAT YOU WILL LEARN:
Clearly define an ML problem
Survey available data resources and identify potential ML applications
Prepare data for effective ML applications
Take a business need and turn it into a machine learning application
Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning
About The Course:
If you are a software developer who wants to build scalable AI-powered algorithms, you need to understand how to use the tools to build them. This course is part of the upcoming Machine Learning in Tensorflow Specialization and will teach you best practices for using TensorFlow, a popular open-source framework for machine learning.
SKILLS YOU WILL GAIN
Computer Vision
Tensorflow
Machine Learning
Developing AI Applications on Azure
About The Course:
This course introduces the concepts of Artificial Intelligence and Machine learning. We’ll discuss machine learning types and tasks, and machine learning algorithms. You’ll explore Python as a popular programming language for machine learning solutions, including using some scientific ecosystem packages which will help you implement machine learning.
SKILLS YOU WILL GAIN
Python Programming
Azure AI models
Microsoft Team Data Sciences Process
Azure Machine Learning Service
Azure Machine Learning Workspace
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