Data Science with NumPy, Sets, and Dictionaries
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.
Monthly Subscription Starting at AED 99 + VAT
- Level Foundation
- Duration 31 hours
- Course by Duke University
-
Offered by
About
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!Modules
Basics of Object Oriented Programming
-
5
Videos
-
1
Readings
-
2
Programming
- Point
- Circle
5
Videos
- Introduction: Representing Data
- Object-Oriented Programming Overview
- Classes
- Constructors
- Modules and Import Statements
1
Readings
- Python Import Does Not Reload Modules
Sets and Big O
-
5
Videos
-
3
Readings
-
2
Programming
- Closest Point
- Count Words
5
Videos
- Sets: Motivation
- Sets in Python
- Dictionaries: Introduction
- Combining Dictionaries with Classes and Sets
- Word Counts: Motivation
3
Readings
- A Bit More About Big O
- Comprehensions
- Introduction to the Interactive Console
Using Vectors in NumPy
-
1
Videos
-
6
Readings
-
1
Quiz
-
2
Lab
2
Labs
- Vector Exercises
- Live Coding Lab: Exploring Vector Data
1
Videos
- Live Coding: Exploring Vector Data
6
Readings
- Why Numpy?
- Working with Vectors
- Math with Vectors
- Histograms
- Type Promotion in numpy
- Vector Recap
1
Quiz
- Vector Exercise Self-Check
Manipulating Vectors
-
3
Readings
3
Readings
- Subsetting Vectors
- Modifying Subsets of Vectors
- Vector Subsets Recap
Module 2 Wrap-Up
-
1
Quiz
-
1
Lab
1
Labs
- Numpy Lab for Answering Quiz Questions
1
Quiz
- Module 2 Numpy Wrap-Up Quiz
Views and Copies in NumPy
-
5
Readings
-
1
Lab
1
Labs
- Exercise: Views and Copies
5
Readings
- Vectors, Matrices and Arrays
- Views and Copies in NumPy
- Working With Views and Copies
- Views and Copies Recap
- Objects and Variables
Working with Matrices
-
1
Videos
-
6
Readings
-
1
Lab
1
Labs
- Playing with Images
1
Videos
- Live Coding Demo: Subsetting and Filtering Matrices
6
Readings
- Matrices
- Reshaping Matrices
- Images as Matrices
- Subsetting Matrices
- Modifying Subsets
- Matrix Recaps
Using ND Arrays
-
3
Readings
3
Readings
- ND Arrays
- Broadcasting
- ND Array Review
Module 3 Wrap-Up
-
1
Quiz
-
1
Lab
1
Labs
- Lab for Answering Module 3 Quiz Questions
1
Quiz
- Module 3 Quiz
Summarizing Arrays
-
5
Readings
-
1
Lab
1
Labs
- Exercise - Remote Sensing
5
Readings
- Moving Past Matrices
- Summarizing Arrays
- Color Images as Arrays
- Examples of Summarizing Arrays
- Exercise - Summarizing Arrays
Vectorization and Randomization
-
1
Videos
-
6
Readings
1
Videos
- Live Coding: Demonstrating Vectorization
6
Readings
- Speed and Ease of Use
- Vectorization
- Exercise - Vectorization
- Random Numbers
- Random Numbers Exercises
- Course Wrap Up: Moving Past NumPy
Module 4 Wrap-Up
-
1
Quiz
-
1
Lab
1
Labs
- Lab for Answering Module 4 Quiz Questions
1
Quiz
- Module 4 Quiz
Auto Summary
Dive into the world of data science with this foundational course on NumPy, sets, and dictionaries. Ideal for aspiring data scientists, software developers, and analysts, you'll master key programming concepts and advanced data structures. With hands-on practice, learn to manipulate and filter large datasets, summarize data, and optimize analysis. Guided weekly assignments ensure skill reinforcement. Taught by Coursera, this 1860-minute course offers a transformative learning experience for beginners. Start your journey today with a Starter subscription!
Genevieve M. Lipp
Nick Eubank
Kyle Bradbury
Andrew D. Hilton