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Updated in [June 30th, 2023]

This course, Machine Learning for Everyone, provides an introduction to the fundamentals of SQL and its use in data analysis. Students will learn how to use SQL queries to investigate topics such as customer preferences, customer engagement, and sales development. The course also covers SQL extensions for online analytical processing (OLAP), which makes obtaining key insights from multidimensional aggregated data easier. The course is based on a case study of an online movie rental company with a database containing customer information, movie ratings, actor background information, and other information. By the end of the course, students will have a better understanding of how to use SQL to make decisions.

[Applications]
After taking this course, students can apply their knowledge of SQL to their own data sets. They can use SQL to analyze customer preferences, customer engagement, and sales development. Additionally, they can use SQL extensions for OLAP to gain insights from multidimensional aggregated data. Students can also use SQL to create reports and dashboards to help them make decisions.

[Career Paths]
The career path recommended to learners of this course is that of a Machine Learning Engineer. A Machine Learning Engineer is responsible for developing and deploying machine learning models to solve real-world problems. They must have a strong understanding of data science, machine learning algorithms, and software engineering. They must also be able to work with large datasets and be able to interpret and explain the results of their models.

The development trend for Machine Learning Engineers is to become more specialized in their field. As machine learning becomes more widely used, the need for engineers with specific skillsets will increase. For example, some Machine Learning Engineers may specialize in natural language processing, while others may specialize in computer vision. Additionally, Machine Learning Engineers will need to stay up to date on the latest technologies and trends in the field in order to remain competitive.

[Education Paths]
The recommended educational path for learners interested in Machine Learning for Everyone is a Bachelor's degree in Computer Science or a related field. This degree will provide learners with the foundational knowledge and skills necessary to understand and apply Machine Learning concepts. Learners will gain an understanding of the fundamentals of computer science, including algorithms, data structures, and programming languages. They will also learn about the principles of Machine Learning, such as supervised and unsupervised learning, deep learning, and reinforcement learning. Additionally, learners will gain an understanding of the various tools and technologies used in Machine Learning, such as Python, TensorFlow, and Keras.

The development trend for Machine Learning is rapidly evolving. As technology advances, so does the need for more sophisticated Machine Learning algorithms and tools. As a result, learners should expect to see an increase in the number of courses and programs available that focus on Machine Learning. Additionally, learners should expect to see an increase in the number of job opportunities related to Machine Learning, as more companies are looking to leverage the power of Machine Learning to improve their operations.

Course Syllabus

What is Machine Learning?

Machine Learning Models

Deep Learning