Best Way To Learn AI Development

 What is Artificial Intelligence (AI)?

Are you thinking of Chappie, Terminator, and Lucy? Sentient, self-aware robots are closer to becoming a reality than you think. Developing computer systems that equal or exceed human intelligence is the crux of artificial intelligence. Artificial Intelligence (AI) is the study of computer science focusing on developing software or machines that exhibit human intelligence. A simple enough definition, right?

Obviously, there is a lot more to it. AI is a broad topic ranging from simple calculators to self-steering technology to something that might radically change the future.

Goals and Applications of AI

The primary goals of AI include deduction and reasoning, knowledge representation, planning, natural language processing (NLP), learning, perception, and the ability to manipulate and move objects. Long-term goals of AI research include achieving Creativity, Social Intelligence, and General (human level) Intelligence.

How can you build your first bot?

You can start learning how to create bots in Python through the following tutorial in the simplest way.

How to build a Python Bot

You can also start by using APIs and tools that offer the ability to build end-user applications. This helps you by actually building something without worrying too much about the theory at first. Some of the APIs that you can use for this are:

Google Cloud Prediction API Documentation

DiffBot

Machine Learning for Language Toolkit

Scrapy

Wolfram Alpha API

Here’s a listing of a few BOT problems for you to practice and try out before you attempt the ultimate challenge.

Tic Tac Toe

Hex

Dots & Boxes

What now?

Once you have a thorough understanding of your preferred programming language and enough practice with the basics, you should start to learn more about Machine Learning. In Python, start learning Scikit-learn, NLTK, SciPy, PyBrain, and Numpy libraries which will be useful while writing Machine Learning algorithms.You need to know Advanced Math and as well.

Here is a list of resources for you to learn and practice:

• A Visual Introduction to Machine Learning
• Machine Learning (By Andrew Ng)
• Machine Learning Lectures (Tom Mitchell)
• Artificial Intelligence (edX) (Specially for practice exercise in Python)
• Intro to Statistics 
• Intro to Artificial Intelligence  (Includes Logic and Robotics)
• Artificial Intelligence

Here are a few more valuable links:

• Artificial Intelligence: A Modern Approach
• AI Algorithms, Data Structures, and Idioms in Prolog, Lisp, and Java
• Computational Cognitive Neuroscience
• Computational Explorations in Cognitive Neuroscience
• 13 Free self-study books on Mathematics, Machine learning, and Deep learning
• 13 Free training courses on Machine learning and Artificial Intelligence
• Data Tools Deep Dive: Machine Learning

You should also take part in various AI and BOT Programming Contests at different places on the Internet:

Kaggle

Coding Game

HackerEarth

Robocup

AI has heavily influenced different sectors that we may not recognize. Ray Kurzweil says “Many thousands of AI applications are deeply embedded in the infrastructure of every industry.” John McCarthy, one of the founders of AI, once said that “as soon as it works, no one calls it AI anymore.”

Broadly, AI is classified into the following: