Artificial intelligence/ Machine learning

Description

Welcome to 9 dollar academy. Artificial Intelligence and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. So what is Machine Learning ? Machine learning is a field in computer science where data are used to predict, or respond to,future data. Machine learning is important in areas such as facial recognition, spam filtering, and other areas where it is not feasible, or even possible, to write algorithms to perform a task.

No prior experience with AI/ML is required, although basic knowledge of Python is desirable. Prior knowledge in Python programming language would be helpful but is not necessary.

Syllabus

• • Concept Lesson – What is Machine Learning?
  • Concept Lesson – Understanding the history of AI and machine learning
  • Concept Lesson – Exploring what machine learning can do for AI
  • Concept Lesson – Considering the goals of machine learning
  • Concept Lesson – Considering the Relationship between AI and Machine Learning
  • Concept Lesson – Overcoming AI Fantasies
  • Concept Lesson – Considering the true uses of AI and machine learning
  • Concept Lesson – Having a Glance at the Future
  • Concept Lesson – Considering the role of machine learning in robots
  • Concept Lesson – Using machine learning in health care
  • Concept Lesson – Creating smart systems for various needs
  • Concept Lesson – Python for Machine Learning
  • Practical Lesson – Running Python
  • Practical Lesson – Install Anaconda
  • Concept Lesson – My First Python Program
  • Practical Lesson – Key Concepts ( Identifiers,Keywords)
  • Practical Lesson – Code Blocks (Indentations)
  • Practical Lesson – Comments in Python
  • Practical Lesson – Basic Operators
  • Practical Lesson – Control Structures
  • Practical Lesson – Lists
  • Practical Lesson – Tuples
  • Practical Lesson – Sets
  • Practical Lesson – Dictionary
  • Practical Lesson – User-Defined Functions
  • Practical Lesson – Modules
  • Practical Lesson – File Input/Output
  • Practical Lesson – Exception Handling
  • Concept Lesson – Knowing your data
  • Concept Lesson – Supervised Learning
  • Concept Lesson – Unsupervised Learning
  • Concept Lesson – Reinforcement Learning
  • Concept Lesson – Introduction to Regression
  • Practical Lesson – Download Scikit-learn library
  • Practical Lesson -Use scikit-learn library to implement Simple linear regression
  • Concept Lesson – Introduction to Classification
  • Concept Lesson – Introduction to Logistic Regression
  • Concept Lesson – Support vector machines (SVMs)
  • Concept Lesson -Decision Tree
  • Concept Lesson – Naïve Bayes Algorithm
  • Concept Lesson – Random forest
  • Concept Lesson – K-Nearest Neighbours
  • Project Lesson -Apply KNN on a real world problem
  • Concept lesson – Intro to Clustering
  • Concept lesson – Summery