Data Science with NumPy, Sets, and Dictionaries
- Offered byCoursera
Data Science with NumPy, Sets, and Dictionaries at Coursera Overview
Duration | 30 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Data Science with NumPy, Sets, and Dictionaries at Coursera Highlights
- Earn a certificate from Duke University
- Add to your LinkedIn profile
- 4 quizzes
Data Science with NumPy, Sets, and Dictionaries at Coursera Course details
- 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!
Data Science with NumPy, Sets, and Dictionaries at Coursera Curriculum
Sets and Dictionaries: Storing and Working with Data
Introduction: Representing Data
Object-Oriented Programming Overview
Classes
Constructors
Modules and Import Statements
Sets: Motivation
Sets in Python
Dictionaries: Introduction
Combining Dictionaries with Classes and Sets
Word Counts: Motivation
Python Import Does Not Reload Modules
A Bit More About Big O
Comprehensions
Introduction to the Interactive Console
Point
Closest Point
Count Words
Circle
NumPy and Vectors
Live Coding: Exploring Vector Data
Why Numpy?
Working with Vectors
Math with Vectors
Histograms
Type Promotion in numpy
Vector Recap
Subsetting Vectors
Modifying Subsets of Vectors
Vector Subsets Recap
Vector Exercise Self-Check
Week 2 Numpy Wrap-Up Quiz
Vector Exercises
Live Coding Lab: Exploring Vector Data
Numpy Lab for Answering Quiz Questions
Matrices and Arrays
Live Coding Demo: Subsetting and Filtering Matrices
Vectors, Matrices and Arrays
Views and Copies in NumPy
Working With Views and Copies
Views and Copies Recap
Objects and Variables
Matrices
Reshaping Matrices
Images as Matrices
Subsetting Matrices
Modifying Subsets
Matrix Recaps
ND Arrays
Broadcasting
ND Array Review
Week 3 Quiz
Exercise: Views and Copies
Playing with Images
Lab for Answering Week 3 Quiz Questions
Summarizing Datasets, Performance Optimization, and Data Randomization
Live Coding: Demonstrating Vectorization
Moving Past Matrices
Summarizing Arrays
Color Images as Arrays
Examples of Summarizing Arrays
Exercise - Summarizing Arrays
Speed and Ease of Use
Vectorization
Exercise - Vectorization
Random Numbers
Random Numbers Exercises
Course Wrap Up: Moving Past NumPy
Week 4 Quiz
Exercise - Remote Sensing
Lab for Answering Week 4 Quiz Questions
Data Science with NumPy, Sets, and Dictionaries at Coursera Admission Process
Important Dates
Other courses offered by Coursera
Student Forum
Anything you would want to ask experts?
Data ScienceData Science BasicsData Science for BusinessData Science with NumPy, Sets, and Dictionaries