Course Description
Machine learning is a subset of AI. Sometimes when we are describing AI, we’re also describing machine learning. AI’s subset, machine learning, the algorithms use a set of training data to enable computers to learn to do something they are not even programmed to do. Machine learning provides us with technology to enlarge our human capabilities.
What are the Stages of AI?
AI is rapidly evolving technology , one reason to get a career in AI provides so much potential. As technology evolves, learning improves.The three stages of AI and machine learning development as follow:
First stage is machine learning : It consists of intelligent systems along with usages of algorithms to learn from experience.
Second Stage is machine intelligence : AI technology dwells now. In this, machines learn from experience based on false algorithms and it is a more evolved form of machine learning, with improved cognitive abilities.
Third Stageis machine consciousness : This is when systems can do self-learning from experience without giving any external data. Siri is an example of machine consciousness.
Course Curriculum:-
Module 1: Introduction to Data Science
Module 2: Introduction to Python
Module 3: Python Basics
Module 4: Python Packages
Module 5: Importing Data
Module 6: Manipulating Data
Module 7: Statistics Basics
Module 8: Error Metrics Data Exchange – Course modules
Module 9: Machine Learning, Supervised Learning, Unsupervised Learning, SVM, SVM Kernal, Other Machine Learning algorithms
Module 10: Artificial Intelligence AI Introduction
- Module 11: Deep Learning Algorithms, Introduction to NLP, Tasks of NLP
Benefits of Artificial Intelligence Training
Artificial intelligence
fundamentals
Computational mathematics for learning and data analysis
Machine learning
Human language technologies
Parallel and distributed systems: paradigms and models
Intelligent Systems for pattern recognition
Algorithm engineering (KD)
Data mining (KD)
Mobile and cyber-physical systems (ICT)
Real-time Data Warehouse migration
Information retrieval (KD)
Social and ethical issues in computer technology
Computational neuroscience (ING)
Robotics
Semantic web
