Learning Python … A Tool for Data Science, Machine Learning, and Computational Thinking
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Dr. Mansour K. Mansour's document discusses learning Python for data science, machine learning, and computational thinking. It covers popular in-demand jobs like data science and machine learning, necessary skills for the Fourth Industrial Revolution like problem solving and critical thinking, programming languages to consider learning like Python and R, career opportunities and salaries in Python, and Python features and IDEs like Jupyter Notebook. The document provides an overview of learning Python and resources for getting started in data science.
![Comparing Java, C++, C#, and Python
10
public class HelloWorld { public
static void main(String[] args) {
// Prints "Hello, World" to the
terminal window.
System.out.println("Hello, World");
}}
#include <iostream>
using namespace std;
int main()
{ cout << "Hello, World!";
return 0; }
using System;
namespace HelloWorld {
class Hello { static void Main()
{ Console.WriteLine("Hello
World!");
} } }
print("Hello, World!")
Java C++
C# Python](https://image.slidesharecdn.com/learningpython-190321142105/85/Learning-Python-A-Tool-for-Data-Science-Machine-Learning-and-Computational-Thinking-10-320.jpg)
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Learning Python … A Tool for Data Science, Machine Learning, and Computational Thinking
- 1. Dr. Mansour K. Mansour March 20, 2019 1 Learning Python … A Tool for Data Science, Machine Learning, and Computational Thinking
- 2. TABLE OF CONTENT 2 Most in Demand Jobs Today – Data Science and Machine Learning What skills are needed for 4IR? 5 Skills Learned from Coding in the Classroom What Programming Language Should I Learn First? Python Career Opportunities Python: Companies vs Salaries Characteristics and Features of Python Comparing Java, C++, C#, and Python Interpreter vs Compiler Top 5 Python IDEs For Data Science Installing Juypter Notebook Samples and Demos
- 3. Most in Demand Jobs Today – Data Science and Machine Learning 3 On Feb. 26, 2019, WorkingNation and The Wharton Customer Analytics Initiative (WCAI) hosted a Town Hall with leaders in business, academia, government, and the non-profit sectors on their talent needs in the area of data analytics and their innovative solutions. According to Allen Blue, Co-founder, LinkedIn - Keynote Speaker, o Data Science and Machine Learning are right there at the top o “The two of them together, represent five of the top 15 growing jobs in America today. So if you look at that list of the top 15, five of them are data and machine learning-related,” o As an example, Blue explains that in San Francisco there are more than 38,000 jobs which need to be filled more than there are people who have the skills to fill them. https://workingnation.com/wharton/
- 4. What skills are needed for 4IR? 4 Preparing tomorrow’s workforce for the Fourth Industrial Revolution: A joint report from Deloitte and the Global Business Coalition for Education highlights opportunities for the business community to address the youth skills gap, and develop the workforce of the future. https://www2.deloitte.com/global/en/page s/about-deloitte/articles/gx-preparing- tomorrow-workforce-for-the-fourth- industrial-revolution.html
- 5. 5 Skills Learned from Coding in the Classroom 5 PROBLEM SOLVING Coding exercises taught in the classroom help students solve complex problems. “It also consists of some very specific problem solving skills such as the ability to think logically, algorithmically and recursively,” says Computer Science for Fun. CRITICAL THINKING Coding can help students build this important skill, since they can’t just start working on the problem at hand. “You can’t just wing it when you’re working on a coding problem. You really have to take the time and energy to look at it and understand it at a different level,” says Jennifer Williams. It’s important for students to map out what they’ll do, and the order in which they’ll complete it. This skill can be transferred to other subjects such as reading comprehension. COMPUTATIONAL THINKING SKILLS According to Computer Science for Fun, computational thinking is a “collection of diverse skills to do with problem solving that result from studying the nature of computation. It includes some obviously important skills that most subjects help develop, like creativity, ability to explain and teamwork.” DETERMINATION In coding, things rarely work the first time. In order to be successful, students learn that it often takes hard work to solve an issue at hand. When they solve the problem, there is an “immediate sense of accomplishment that students realize when they succeed. They’ve overcome a challenge and receive instant acknowledgment and gratification – it’s the same reason many students (and adults) addictively play games,” says Dan Kusan. COURAGE TO TRY NEW THINGS Coding helps students gain the courage to try new things. A benefit about coding is that students often fail before being successful. This requires them to try out new ideas until one sticks. And “coding has no “right way” or defined path, which allows the freedom for students to succeed on their own time and in their own way,” according to STEMJobs. https://edurolearning.com/5-skills-learned-coding-classroom/
- 6. What Programming Language Should I Learn First? … Factors to Consider 6 • It depends on the location and industry • Gaming or banking – C# or C++ • Data Scientist – Python, R, Java, Matlab • Check job postings on LinkedIn or Indeed or Glassdoor Job Market • (iOS Apps -> Swift), (Android Apps -> Java, Kotlin) • (Websites -> JavaScript, HTML, CSS) • (Data, Engineering, Science -> Python, R, Matlab) • (Game Development -> C++, C#) What do you want to build? • Python is easier than C++ or C • JavaScript is easier than Java Ease of Learning
- 8. Python: Companies vs Salaries 8 • Instagram • Google • Spotify • Netflix • Uber • Dropbox • Pinterest • Instacart • Reddit • Lyft https://learn.onemonth.com/10-famous-websites-built-using-python/
- 9. Characteristics and Features of Python 9 Created by Guido van Rossum and first released in 1991, Python has a design philosophy that emphasizes code readability, notably using significant whitespace. Interpreted Language: Python is processed at runtime by Python Interpreter. Object-Oriented Language: It supports object-oriented features and techniques of programming. Interactive Programming Language: Users can interact with the python interpreter directly for writing programs. Easy language: Python is easy to learn language especially for beginners. Straightforward Syntax: The formation of python syntax is simple and straightforward which also makes it popular. Easy to read: Python source- code is clearly defined and visible to the eyes. Portable: Python codes can be run on a wide variety of hardware platforms having the same interface. Extendable: Users can add low level-modules to Python interpreter. Scalable: Python provides an improved structure for supporting large programs then shell-scripts. https://www.w3schools.in/python-tutorial/overview/
- 10. Comparing Java, C++, C#, and Python 10 public class HelloWorld { public static void main(String[] args) { // Prints "Hello, World" to the terminal window. System.out.println("Hello, World"); }} #include <iostream> using namespace std; int main() { cout << "Hello, World!"; return 0; } using System; namespace HelloWorld { class Hello { static void Main() { Console.WriteLine("Hello World!"); } } } print("Hello, World!") Java C++ C# Python
- 11. Interpreter vs Compiler 11 A program written in high-level language is called a source code. We need to convert the source code into machine code and this is accomplished by compilers and interpreters. Hence, a compiler or an interpreter is a program that converts program written in high- level language into machine code understood by the computer. https://www.programiz.com/article/difference-compiler-interpreter
- 12. Top 5 Python IDEs For Data Science 12 Spyder contains features like a text editor with syntax highlighting, code completion and variable exploring, which you can edit its values using a Graphical User Interface (GUI). PyCharm has interesting features such as a code editor, errors highlighting, a powerful debugger with a graphical interface, besides of Git integration, SVN, and Mercurial. Thonny supports code completion and highlight syntax errors, but it also provides a simple debugger, which you can run your program step- by-step. Atom One of the best advantages of Atom is its community, chiefly due to the constants enhancements and plugins that they develop in order to customize your IDE and improve your workflow. Jupyter Notebook supports markdowns, allowing you to add HTML components from images to videos. Thanks to Jupyter, you can easily see and edit your code in order to create compelling presentations. https://www.datacamp.com/community/tutorials/data-science-python-ide
- 13. Installing Juypter Notebook 13 o Go to https://www.anaconda.com/distribution/ to download the Anaconda package manager o Choose the platform: Windows | macOS | Linux o Download Python 3.7 Version
- 14. Samples and Demos 1 - Introduction To Lists In Python 14
- 15. Samples and Demos 2 - Data Visualizations 15
- 16. TOGETHER WE SUCCEED. THANK YOU 16