Computing for Data Analysis (CourseraArchive) 7 个评论 关注

开始时间: 04/22/2022 持续时间: 4 weeks

主页: https://www.coursera.org/course/compdata

简介: This course is about learning the fundamental computing skills necessary for effective data analysis. You will learn to program in R and to use R for reading data, writing functions, making informative graphs, and applying modern statistical methods.

Algorithms: Design and Analysis, Part 2 (CourseraArchive) 4 个评论 关注

开始时间: 04/22/2022 持续时间: 6 weeks

主页: https://www.coursera.org/course/algo2

简介: In this course you will learn several fundamental principles of advanced algorithm design: greedy algorithms and applications; dynamic programming and applications; NP-completeness and what it means for the algorithm designer; the design and analysis of heuristics; and more.

Pattern Discovery in Data Mining (CourseraArchive) 1 个评论 关注

开始时间: 04/22/2022 持续时间: 4 weeks

主页: https://www.coursera.org/course/patterndiscovery

简介: Learn the basic concepts of data mining and dive deep into pattern discovery methods and their applications.

機器學習技法 (Machine Learning Techniques) (CourseraArchive) 2 个评论 关注

开始时间: 04/22/2022 持续时间: 8 weeks

主页: https://www.coursera.org/course/ntumltwo

简介: The course extends the fundamental tools in "Machine Learning Foundations" to powerful and practical models by three directions, which includes embedding numerous features, combining predictive features, and distilling hidden features. [這門課將先前「機器學習基石」課程中所學的基礎工具往三個方向延伸為強大而實用的工具。這三個方向包括嵌入大量的特徵、融合預測性的特徵、與萃取潛藏的特徵。]

算法设计与分析 Design and Analysis of Algorithms (CourseraArchive) 0 个评论 关注

开始时间: 04/22/2022 持续时间: 13 weeks

主页: https://www.coursera.org/course/algorithms

简介: 学习面对实际问题如何设计算法与分析算法。

Combinatorial Mathematics (EdxArchive) 0 个评论 关注

开始时间: 04/22/2022 持续时间: 11 weeks

主页: https://www.edx.org/archive/combinatorial-mathematics-tsinghuax-60240013x-0

简介: 60240013x will not only provide a thorough understanding of the counting principles in our daily life, but also discover how the math knowledge could be applied in many areas such as computer science, and financial analysis.