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所在平台: Udemy |
课程主页: https://www.udemy.com/course/100-days-of-code-data-scientist-challenge/
课程评论：没有评论
Coursera 上的《100天Python数据科学家挑战》课程是一项为期100天、以实践为导向的密集型学习计划，旨在帮助学习者在100天内成为熟练的数据科学家。本课程遵循著名的#100DaysOfCode挑战，鼓励学员连续100天每天投入至少一小时进行数据科学编码任务。 该课程采用“边做边学”的学习方法，通过每天的新任务，让学生深入探索数据科学的各个方面，包括数据提取、预处理、建模、分析和可视化。这些练习基于真实世界的场景，涵盖从简单任务到复杂问题，涉及数据清洗、探索性数据分析、机器学习、深度学习等主题。 课程广泛使用Pandas、NumPy、Matplotlib、Seaborn和Scikit-Learn等Python库，并深入介绍自然语言处理（NLP）、时间序列分析和神经网络等高级概念。超过100个动手练习将帮助学生巩固数据科学理论知识，培养实际编码技能和解决问题的能力，为在实际工作中做好准备。 通过每天的编码和解决问题，学生将加深对所学概念的理解。完成100天的学习后，学生将建立一个能够展示其解决各类数据科学问题的能力的作品集，证明他们已为数据科学行业做好准备。 这门课程是您用Python开启数据科学之旅的理想选择。无论您是初学者还是希望提升技能，这个为期100天的挑战都将为您提供必要的工具和信心，助您在数据科学领域取得成功。
This course is an intensive, practical-oriented program that aims to transform learners into proficient data scientists within 100 days. This course follows the recognized #100DaysOfCode challenge, inviting participants to engage in data science coding tasks for a minimum of an hour daily for 100 consecutive days. This course allows students to take a hands-on approach in learning data science, featuring a multitude of practical exercises spanning 100 days.Each day of the challenge presents a fresh set of tasks, each tailored to explore various facets of data science including data extraction, preprocessing, modeling, analysis, and visualization. These exercises are set within the context of real-world scenarios, and range from simple tasks to more complex problems, covering topics such as data cleaning, exploratory data analysis, machine learning, deep learning, and more.This course covers a wide range of Python libraries like Pandas, NumPy, Matplotlib, Seaborn, and Scikit-Learn, and it does not shy away from introducing the students to more advanced concepts such as Natural Language Processing (NLP), Time-Series Analysis, and Neural Networks.With over 100 hands-on exercises, the students will be able to solidify their understanding of data science theory, develop practical coding skills and problem-solving abilities that will be crucial in a real job setting.This course encourages a "learn by doing" approach, where students will be coding and solving problems each day, thus reinforcing the concepts learned. By the end of the 100 days, students will have built a robust portfolio showcasing their ability to tackle a variety of data science problems, proving to potential employers their readiness for the data science industry.100 Days of Code: Your Data Science Journey in PythonEmbark on a transformative 100-day coding challenge designed to build and sharpen your data science skills using Python. From foundational programming and data manipulation to machine learning and real-world projects, each day offers hands-on exercises, practical applications, and guided learning. Whether you're a beginner or looking to upskill, this journey will equip you with the tools and confidence to thrive as a data scientist.
