Become proficient in NumPy, a fundamental Python package crucial for careers in data science. This comprehensive course is tailored to novice programmers aspiring to become data scientists, software developers, data analysts, machine learning engineers, data engineers, or database administrators.
Starting with foundational computer science concepts, such as object-oriented programming and data organization using sets and dictionaries, you'll progress to more intricate data structures like arrays, vectors, and matrices. Hands-on practice with NumPy will equip you with essential skills to tackle big data challenges and solve data problems effectively. You'll write Python programs to manipulate and filter data, as well as create useful insights out of large datasets.
By the end of the course, you'll be adept at summarizing datasets, such as calculating averages, minimums, and maximums. Additionally, you'll gain advanced skills in optimizing data analysis with vectorization and randomizing data.
Throughout your learning journey, you'll use many kinds of data structures and analytic techniques for a variety of data science challenges , including mathematical operations, text file analysis, and image processing. Stepwise, guided assignments each week will reinforce your skills, enabling you to solve problems and draw data-driven conclusions independently.
Prepare yourself for a rewarding career in data science by mastering NumPy and honing your programming prowess. Start this transformative learning experience today!
This module, you will learn the basics of object oriented programming as well as how to use sets and dictionaries to store and work with data in Python. You will apply these concepts with Python to perform some mathematical operations and analytical tasks, including solving geometric problems with circles and counting words in a document.
涵盖的内容
10个视频5篇阅读材料4个编程作业
显示有关单元内容的信息
10个视频•总计41分钟
Introduction: Representing Data•1分钟
Object-Oriented Programming Overview•4分钟
Classes•4分钟
Constructors•3分钟
Modules and Import Statements•2分钟
Sets: Motivation•6分钟
Sets in Python•7分钟
Dictionaries: Introduction•4分钟
Combining Dictionaries with Classes and Sets•7分钟
Word Counts: Motivation•3分钟
5篇阅读材料•总计45分钟
Python Import Does Not Reload Modules•10分钟
Report a problem with the course•5分钟
A Bit More About Big O•10分钟
Comprehensions•10分钟
Introduction to the Interactive Console•10分钟
4个编程作业•总计720分钟
Point•180分钟
Closest Point•180分钟
Count Words•180分钟
Circle•180分钟
NumPy and Vectors
第 2 单元•小时 后完成
单元详情
This module, you will learn how to utilize NumPy--one of the most useful Python packages we use in data science--as well as learn additional data structures, arrays, beginning with the simplest type of an array, a vector. With NumPy and your new understanding of vectors, you will develop histograms as well as analyze household income distribution data in the United States, drawing your own data-driven conclusions.
涵盖的内容
1个视频9篇阅读材料2个作业3个非评分实验室
显示有关单元内容的信息
1个视频•总计22分钟
Live Coding: Exploring Vector Data•22分钟
9篇阅读材料•总计90分钟
Why Numpy?•10分钟
Working with Vectors•10分钟
Math with Vectors•10分钟
Histograms•10分钟
Type Promotion in numpy•10分钟
Vector Recap•10分钟
Subsetting Vectors•10分钟
Modifying Subsets of Vectors•10分钟
Vector Subsets Recap•10分钟
2个作业•总计60分钟
Vector Exercise Self-Check•30分钟
Module 2 Numpy Wrap-Up Quiz•30分钟
3个非评分实验室•总计180分钟
Vector Exercises•60分钟
Live Coding Lab: Exploring Vector Data•60分钟
Numpy Lab for Answering Quiz Questions•60分钟
Matrices and Arrays
第 3 单元•小时 后完成
单元详情
This module, you will first learn how NumPy handles data in your program using views and copies of your data. You will then learn how to work with more complex arrays called matrices, as well as how you can subset, filter, and modify data in matrices. Finally, you will write your own programs to manipulate data matrices and report your results for a given dataset.
涵盖的内容
1个视频14篇阅读材料1个作业3个非评分实验室
显示有关单元内容的信息
1个视频•总计13分钟
Live Coding Demo: Subsetting and Filtering Matrices •13分钟
14篇阅读材料•总计140分钟
Vectors, Matrices and Arrays•10分钟
Views and Copies in NumPy•10分钟
Working With Views and Copies•10分钟
Views and Copies Recap•10分钟
Objects and Variables•10分钟
Matrices•10分钟
Reshaping Matrices•10分钟
Images as Matrices•10分钟
Subsetting Matrices•10分钟
Modifying Subsets•10分钟
Matrix Recaps•10分钟
ND Arrays•10分钟
Broadcasting•10分钟
ND Array Review•10分钟
1个作业•总计60分钟
Module 3 Quiz•60分钟
3个非评分实验室•总计180分钟
Exercise: Views and Copies•60分钟
Playing with Images•60分钟
Lab for Answering Module 3 Quiz Questions•60分钟
Summarizing Datasets, Performance Optimization, and Data Randomization
第 4 单元•小时 后完成
单元详情
In this module, you will learn how to use NumPy to summarize data from matrices (e.g., calculating averages, minimums, maximums, etc.) as well as how to begin to analyze and manipulate image data. You will also explore two new data science techniques: how to make your analysis of data matrices more computationally efficient (vectorization) and how to randomize data (randomization).
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
When will I have access to the lectures and assignments?
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.