Learn Data Science and Machine Learning on Microsoft Azure

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Cost

Free
Provider

Udemy
Certificate

No Information
Language

English
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3.0

2,400 Ratings

Learn how to use Microsoft Azure to become a data science and machine learning expert. With Power BI, Power Query, and Python, you can create visualisations, clean data, and create advanced charts and analyses. Plus, use Azure cloud for Text Analytics and create machine learning instances for computer vision. Take your data science and machine learning skills to the next level with Microsoft Azure.

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Learn Data Science and Machine Learning on Microsoft Azure

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Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [June 30th, 2023]

This course provides an introduction to Data Science and Machine Learning on Microsoft Azure. Participants will learn how to use Power BI to create visualisation charts and business intelligence reports, as well as how to use Power Query to perform data cleaning operations. Additionally, participants will learn how to use Python in Power BI to create advanced charts and analyses. Furthermore, participants will learn how to create machine learning instances for computer vision in Azure, and use Microsoft Azure cloud for Text Analytics.

[Applications]
After completing this course, students can apply their knowledge to create visualisations and reports in Power BI, clean data with Power Query, create advanced charts and analyses with Python, create machine learning instances for computer vision in Azure, and use Microsoft Azure cloud for Text Analytics. Additionally, students can use their knowledge to develop applications that use data science and machine learning on Microsoft Azure.

[Career Paths]
One job position path that is recommended for learners of this course is Data Scientist. Data Scientists are responsible for collecting, analyzing, and interpreting large amounts of data to identify trends and patterns. They use a variety of techniques, such as machine learning, natural language processing, and statistical analysis, to uncover insights from data. Data Scientists also develop predictive models and algorithms to help organizations make better decisions.

The development trend for Data Scientists is to become more specialized in their field. As data becomes more complex and data sources become more diverse, Data Scientists need to be able to understand and interpret data from a variety of sources. They also need to be able to use advanced techniques such as deep learning and artificial intelligence to uncover insights from data. Additionally, Data Scientists need to be able to communicate their findings to stakeholders in a clear and concise manner.

[Education Paths]
The recommended educational path for learners interested in data science and machine learning on Microsoft Azure is a Bachelor's degree in Computer Science or a related field. This degree will provide learners with the foundational knowledge and skills needed to understand and apply data science and machine learning concepts.

The curriculum of a Bachelor's degree in Computer Science or a related field typically includes courses in programming, algorithms, data structures, databases, operating systems, computer networks, artificial intelligence, and software engineering. Additionally, courses in mathematics, statistics, and machine learning are often included.

The development trend of this educational path is to focus on the application of data science and machine learning concepts in the context of cloud computing. This includes learning how to use cloud-based tools such as Microsoft Azure to create and deploy machine learning models, as well as how to use cloud-based services to store and analyze large datasets. Additionally, learners should be familiar with the latest technologies and trends in the field, such as deep learning and natural language processing.

Course Syllabus

Getting started with Power BI

Interactive charts and Drill Down Analysis

Customizing Dataset with Calculated Field, Slicers

Storytelling with Animated charts

Data Cleaning with Power Query

Creating Advanced charts using Python Matplotlib

Azure Machine Learning- Computer Vision

Azure Machine Learning- Text Analytics

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Pros & Cons

Comprehensive coverage of data science and machine learning.
Engaging and interesting course content.
Practical hands-on exercises and projects.

Lack of attention to specific lesson topics.
Inadequate explanation of the course title.
Potential confusion in lesson 19.

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