Northeastern University
Data Analytics Engineering: Probability & Techniques
Northeastern University

Data Analytics Engineering: Probability & Techniques

Sri Radhakrishnan

位教师:Sri Radhakrishnan

包含在 Coursera Plus

深入了解一个主题并学习基础知识。
2 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
为学位做准备
深入了解一个主题并学习基础知识。
2 周 完成
在 10 小时 一周
灵活的计划
自行安排学习进度
为学位做准备

了解顶级公司的员工如何掌握热门技能

Petrobras, TATA, Danone, Capgemini, P&G 和 L'Oreal 的徽标

该课程共有4个模块

In this module, we will focus on Python programming fundamentals. The aim is to help understand Python's basic syntax, data types, and operators, enabling the creation of simple programs. Additionally, we will cover the use of if statements, loops, and proper indentation to control program flow, fostering a foundational understanding of essential control structures in Python programming.

涵盖的内容

5个视频7篇阅读材料1个作业1个编程作业1个讨论话题

In this module, we will dive into the diverse landscape of Python data structures, including lists, dictionaries, sets, tuples, and arrays. By exploring real-world use cases, you will uncover the unique strengths and weaknesses of each data structure. You will gain insights into recognizing and understanding the characteristics of these structures, empowering you to make informed choices when tackling programming challenges. Through hands-on practice, you will develop the skills to select and apply the most suitable data structure to efficiently solve a wide range of problems, enhancing your proficiency in Python programming.

涵盖的内容

2个视频3篇阅读材料1个测验1个编程作业

In this module we will introduce DataFrames, a pivotal tool in data manipulation and analysis. You will grasp the fundamental concepts of DataFrames, learning how to create, manipulate, and access data efficiently. You will gain essential skills for basic data exploration–including summarizing data, indexing, and slicing, enabling them to extract meaningful insights. Furthermore, this module equips learners with the expertise to clean and preprocess data, covering handling missing values, filtering data, merging/joining datasets, and transforming data for analysis readiness. By the end of this module, you will harness DataFrames for advanced data analysis, mastering group-wise operations, aggregation, and statistical analysis.

涵盖的内容

3个视频4篇阅读材料1个作业1个编程作业

This module will equip you with a comprehensive toolkit for proficient data exploration and analysis. It covers the essential techniques and tools for effectively summarizing data sets, encompassing statistical summaries, data visualization, and data cleaning methods. You will learn how to identify and assess missing data, outliers, and anomalies, vital tasks during the initial exploratory phase of data analysis. Furthermore, you will develop the ability to uncover patterns, relationships, and trends within the data using various visualizations, including scatter plots, histograms, and correlation matrices, enabling them to extract valuable insights and make informed decisions from their data.

涵盖的内容

2个视频2篇阅读材料1个作业1个编程作业

为学位做准备

学习 Northeastern University 的这个 课程,您可以预览相关学位课程计划中的主题、材料和授课教师,以便您确定该主题或大学是否适合您。

 

位教师

Sri Radhakrishnan
Northeastern University
1 门课程796 名学生

提供方

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