Microsoft's New Role-based Azure Certifications
This free course is open to anyone interested in Azure certification. It explains Microsoft's new role-based Azure certification options.
Cybersecurity in Azure with Security Center
Learn about Azure Security and how it supports security for cloud and on-premises services—a must for current and prospective cybersecurity professionals.
Azure Storage 101
Get an overview of Azure Storage Fundamentals and learn about the different types of data storage models in this course for IT professionals.
Introduction to Python and Its Libraries
About this Course:
In this course students will gain the knowledge and skills needed to implement the basics of python data structures with an intuitive understanding of every library required for machine learning. python is one of the best programming choices for data science, machine learning, and deep learning. Python presents a wide array of choices for the completion of each task. It is highly accessible and one of the best ways to get started with programming because it is simple to use as well as quite easy to learn. It also has a great community with constant updates and upgrades. At the writing of this article, the most recent version of python is 3.8
Course Objectives:
After completing this course, students will be able to:
- General Introduction to the Python Language
- How to display data (histograms, scatter plots, line plots etc.)
- Matrix multiplication, Numpy functions, mathematics
- How to manage & edit dataframes
- Pandas
- Numpy
- Matloplib
Audience:
- Students should have at least one year of hands-on experience with Python programming
Prerequisites:
Before attending this course, students must have knowledge of:
- Introduction to Python for Absolute beginner
How to Set Up Your Own Cloud Server from Scratch
This course will comprehensively cover each aspect of running a cloud server.
Common Machine Learning Models
This course will likely be rather lecture heavy with short implementation exercises. Since users should already be familiar with python & be able to work with datasets.
Introduction to Machine Learning
Machine learning is a subfield of artificial intelligence (AI). Machine learning algorithms instead allow for computers to train on data inputs and use statistical analysis in order to output values that fall within a specific range.
First Models and Tests
This course focuses on the data science part, how do we find relevant data, what can we use PCR for, etc. After this course, users should be able to understand datasets and determine/fix problems with them.
Natural Language Processing
Natural language processing (NLP) and text mining are the art and science of extracting insights from large amounts of natural language.
Neural Networks 1
This Course will cover basic neural network architectures and learning algorithms, for applications in pattern recognition, image processing, and computer vision.
