Intro to Data Science & Machine Learning
Join us to learn the fundamentals of data science and machine learning and gain the skills to become a data scientist. ▼
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Course Feature
Cost:
Free
Provider:
Edx
Certificate:
Paid Certification
Language:
English
Start Date:
Self paced
Course Overview
❗The content presented here is sourced directly from Edx 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 introduces students to the world of data science and covers all the major aspects of deriving insights from data sets. Students will learn how to acquire data, clean it for easier analysis, explore and derive insights, convert it into specific features, and model it using machine learning algorithms. The course will be presented almost entirely in Jupyter notebook form, which is one of the primary tools used by data scientists today. Interactive notebooks will be used to test and exercise every aspect of the data science. The course takes a top down approach towards teaching, starting with a complete worked example and then unpacking it to understand each component. By the end of the course, students will be able to write the entire example from scratch on their own.
[Applications]
Upon completion of this course, students should be able to apply the concepts of data science and machine learning to their own projects. They should be able to acquire data, clean it, explore and derive insights, convert it into specific features, and model it using machine learning algorithms. Additionally, they should be able to use insights and predictions from their models to make definitive statements about their data.
[Career Paths]
[Answer]One job position path that is recommended to learners of this course is a Data Scientist. A Data Scientist is a professional who uses data to gain insights and make predictions. They use a variety of tools and techniques to analyze data, such as machine learning algorithms, statistical analysis, and data visualization. Data Scientists are responsible for collecting, cleaning, and organizing data, as well as developing models and algorithms to make predictions and draw insights from the data. They must also be able to communicate their findings to stakeholders in a clear and concise manner.
The development trend for Data Scientists is very positive. As businesses become increasingly data-driven, the demand for Data Scientists is growing rapidly. Companies are looking for Data Scientists who can help them make better decisions and gain a competitive edge. As a result, Data Scientists are in high demand and the job market is expected to continue to grow in the coming years.
[Education Paths]
[Recommended Educational Path]
The recommended educational path for learners interested in data science and machine learning is to pursue a Bachelor's degree in Computer Science or a related field. This degree will provide the foundational knowledge and skills necessary to understand the concepts and techniques used in data science and machine learning. Additionally, courses in mathematics, statistics, and programming will be beneficial.
Once the foundational knowledge is acquired, learners should consider pursuing a Master's degree in Data Science or Machine Learning. This degree will provide a more in-depth understanding of the topics covered in the introductory course, as well as more advanced topics such as deep learning, natural language processing, and reinforcement learning.
Finally, learners should consider pursuing a PhD in Data Science or Machine Learning. This degree will provide the most comprehensive understanding of the topics covered in the introductory course, as well as the most up-to-date research and development trends in the field.
The development trend in data science and machine learning is towards more sophisticated algorithms and techniques, as well as more efficient and powerful computing resources. As the field continues to evolve, learners should stay up-to-date on the latest research and development trends in order to stay ahead of the curve.
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