Microsoft has launched a free MIT-approved learning course titled “Machine Learning For Beginners” to teach students the basics of machine learning. The course duration is 12 weeks.
Azure Cloud advocates and Microsoft student ambassador authors, contributors and reviewers put together the lesson plan that uses pre and post lesson quizzes, videos, knowledge checks, infographics, sketch notes and assignments to equip the students with machine learning skills. The curriculum aims to teach classic machine learning using Scikit-learn as a resource library.
The introduction to ML breaks down the key concepts of machine learning, history, introduction to tools and techniques and also the concept of fairness and data bias in ML. The curriculum covers Reinforcement Learning, Natural Language Processing, Time Series Forecasting, Clustering, Regression and Classification with hands-on practical lessons to teach how to use the models inside web applications.
The curriculum covers:
- What techniques do ML researchers use to build ML models?
- Getting started with Python and Scikit-learn for regression models
- Visualization and clean data in preparation for ML
- Build linear and polynomial regression models
- Build a web app to use your trained model
- Sentiment analysis
- Real-world applications of classical ML
Find the full curriculum here: https://github.com/microsoft/ML-For-Beginners
Microsoft in education
Last year Microsoft launched an initiative to help 25 million people worldwide to acquire digital skills in the pandemic economy. Software development, graphic designing, data analysis, financial analysis and IT administration were among the 10 jobs identified with the greatest number of job openings and steady growth in the past four years. The initiative underlines the importance of digital skills to navigate the post pandemic world.
Microsoft has also listed a few courses on the edX platform. The courses are taught by Microsoft experts and offer hands-on experience with broad reach, cutting-edge technologies in areas including cloud services, mobile development, and data sciences. The courses, ideal for students and working professionals, teaches how to build innovative applications, services, and experiences on the Microsoft platform.
Education must adapt to the fourth industrial revolution. The World Economic Forum posits that 54% of employees will require significant reskilling by 2022. Udemy’s Global Skills Gap Report finds narrowing the skill gap is imperative to staying employed.
For platforms, it is easier to update and scale up learning models to make data science accessible and cost-effective.
Companies like Microsoft want to help fill the demand for digitally skilled workforces. As a part of Microsoft’s global initiative launched in 2020, the company aims to do the following:
- Use data to research and identify in-demand jobs and the skill set required for the same
- To provide free access to develop skills
- To provide free job-seeking tool and low-cost certifications to aid the process
Students, to use this curriculum, fork the entire repo to your own GitHub account and complete the exercises on your own or with a group:
- Start with a pre-lecture quiz
- Read the lecture and complete the activities, pausing and reflecting at each knowledge check.
- Try to create the projects by comprehending the lessons rather than running the solution code; however that code is available in the /solution folders in each project-oriented lesson.
- Take the post-lecture quiz
- Complete the challenge
- Complete the assignment
- After completing a lesson group, visit the Discussion board and “learn out loud” by filling out the appropriate PAT rubric. A ‘PAT’ is a Progress Assessment Tool that is a rubric you fill out to further your learning. You can also react to other PATs so we can learn together.
For further study, following the Microsoft Learn modules and learning paths.
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I am a literature, media and psychology grad which explains much of my confusion in life. I like writing, especially about music. You'll find me clicking photographs and playing music on my guitar most of the time!