If you are over 45 like I do, Artificial Intelligence has a special maybe apocalyptic meaning. After all, we all seen the Terminator and we know AI powered bots are out there to kill us and establish the AI supremacy.
However, if you are not living in a Facebook induced conspiracy theory and you are a technical guy, then you should probably know that while AI systems start to learn on their own using Machine Learning.
Machine Learning is a system that uses computer algorithms to analyze data and make “intelligent decisions” on what it has learned without being explicitly programmed. So basically AI is using mathematics to interpret the World, based on computer algorithms created by humans.
So IT people have to learn how to program AI. Here is a list of free AI courses you can take. (I’ve also got a list of free AI courses for non-technical people)
Python Basics for Data Science on Edx will help you kickstart your learning of Python for data science, as well as programming in general, with this beginner-friendly introduction to Python
Introduction to Machine Learning offer you a foundational understanding of machine learning models (logistic regression, multi layer perceptrons, convolutional neural networks, natural language processing when used for medical diagnostics to image recognition to text prediction.
Applied Machine Learning in Python is offered by University of Michigan and is focusing more on the techniques and methods, dimensionality of data and the task of clustering data using python code to carry out an analysis.
Machine Learning Basics taught by Jaekwang KIM, Assistant Professor at Sungkyunkwan University, helps you understand the basic concepts of machine learning, the K nearest neighbor method, linear regression, model analysis.
Python Data Analysis by Rice University is an introduction to Python programming for reading, storing, and processing tabular data which is the base for further extend your Python programming knowledge and allow you to process more complex data.
Python Data Visualization also by Rice University teaches you how to install external packages for use within Python, acquire data from sources on the Web, and then we will clean, process, analyze, and visualize that data.
MIT has an interesting course on Computer Science and Programming Using Python that talks about Advanced programming in Python 3, Knapsack problem, Graphs and graph optimization, Probability, Distributions, Monte Carlo simulations, Curve fitting and is aimed at students with some prior programming experience.
Machine Learning Fundamentals talks about the theory behind the probabilistic and statistical foundations of data science, decision trees, boosting, and random forests, generative modeling for classification, taxonomy of prediction problems
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