PYTHON-WRK.AJ2 ISBN-Nummer: 978-1-64459-600-5
Python Workshop
Learn the most versatile programming language extensively used by tech giants like Google, Facebook, and Nasa.
What you will be able to do
- Expertise with R programming fundamentals including basic syntax, data structures, control flow, functions & packages
- Skilled at data manipulation, and analysis including import, export, cleaning, processing & exploration
- Ability to perform statistical analysis including descriptive statistics, hypothesis testing, correlation, regression
- Expert at machine learning with decision trees, random forests, support vector machines, neural networks, and clustering
- Create data visualizations using ggplot2 and base R graphics
- Ability to use the shiny framework to build interactive web apps
Beginner Selbstgesteuert · 1 Jahr Zugang
44 Praktische LiveLabs
Practice real IT tasks in guided environments.
- Reale Umgebungen
- Automatisch bewertet
- Keine Installation
01 / About
Über diesen Kurs
Python’s popularity isn’t just a trend. It’s here to rule the world of programming! Join our Python Workshop to learn this versatile coding language that powers technology worldwide.
The comprehensive syllabus covers everything from the fundamentals to Object-Oriented Programming (OOP), advanced Python concepts to data science & machine learning.
You’ll be building dynamic apps using frameworks like Django and Flask You’ll get hands-on coding practice with our Lab projects, solving coding challenges, and building your own Python apps.
02 / Lektionen & Labore
See exactly what you will learn and practice
Unterrichtsplan
12 Interaktive Lektionen · 98 topics01 Introduction 1 topics +
- About the Course
02 Vital Python – Math, Strings, Conditionals, and Loops 11 topics · 7 LiveLab +
- Introduction
- Vital Python
- Numbers: Operations, Types, and Variables
- Python as a Calculator
- Strings: Concatenation, Methods, and input()
- String Interpolation
- String Indexing and Slicing
- Slicing
- Booleans and Conditionals
- Loops
- Summary
7 LiveLab in this lesson — see the labs panel →
03 Python Structures 10 topics · 6 LiveLab +
- Introduction
- The Power of Lists
- Matrix Operations
- List Methods
- Dictionary Keys and Values
- Dictionary Methods
- Tuples
- A Survey of Sets
- Choosing Types
- Summary
6 LiveLab in this lesson — see the labs panel →
04 Executing Python – Programs, Algorithms, and Functions 11 topics · 7 LiveLab +
- Introduction
- Python Scripts and Modules
- Python Algorithms
- Basic Functions
- Iterative Functions
- Recursive Functions
- Dynamic Programming
- Helper Functions
- Variable Scope
- Lambda Functions
- Summary
7 LiveLab in this lesson — see the labs panel →
05 Extending Python, Files, Errors, and Graphs 7 topics · 5 LiveLab +
- Introduction
- Reading Files
- Writing Files
- Preparing for Debugging (Defensive Code)
- Plotting Techniques
- The Don'ts of Plotting Graphs
- Summary
5 LiveLab in this lesson — see the labs panel →
06 Constructing Python – Classes and Methods 8 topics · 3 LiveLab +
- Introduction
- Classes and Objects
- Defining Classes
- The __init__ method
- Methods
- Properties
- Inheritance
- Summary
3 LiveLab in this lesson — see the labs panel →
07 The Standard Library 9 topics · 2 LiveLab +
- Introduction
- The Importance of the Standard Library
- Dates and Times
- Interacting with the OS
- Using the subprocess Module
- Logging
- Collections
- Functools
- Summary
2 LiveLab in this lesson — see the labs panel →
08 Becoming Pythonic 9 topics · 4 LiveLab +
- Introduction
- Using List Comprehensions
- Set and Dictionary Comprehensions
- Default Dictionary
- Iterators
- Itertools
- Generators
- Regular Expressions
- Summary
4 LiveLab in this lesson — see the labs panel →
09 Software Development 7 topics · 2 LiveLab +
- Introduction
- Debugging
- Automated Testing
- Creating a PIP Package
- Creating Documentation the Easy Way
- Source Management
- Summary
2 LiveLab in this lesson — see the labs panel →
10 Practical Python – Advanced Topics 9 topics · 2 LiveLab +
- Introduction
- Developing Collaboratively
- Dependency Management
- Deploying Code into Production
- Multiprocessing
- Parsing Command-Line Arguments in Scripts
- Performance and Profiling
- Profiling
- Summary
2 LiveLab in this lesson — see the labs panel →
11 Data Analytics with pandas and NumPy 8 topics · 4 LiveLab +
- Introduction
- NumPy and Basic Stats
- Matrices
- The pandas Library
- Data
- Null Values
- Visual Analysis
- Summary
4 LiveLab in this lesson — see the labs panel →
12 Machine Learning 8 topics · 2 LiveLab +
- Introduction
- Introduction to Linear Regression
- Cross-Validation
- Regularization: Ridge and Lasso
- K-Nearest Neighbors, Decision Trees, and Random Forests
- Classification Models
- Boosting Methods
- Summary
2 LiveLab in this lesson — see the labs panel →
Praktische Übungen Our edge
44 LiveLabs- Finding the LCM
- Assigning Values to a Variable
- Calculating the Pythagorean Distance between Three Points
- Displaying Strings in Python
- Using the input() Function
- Using the if-else Syntax
- Using the for Loop
- Using a Nested List to Store Employee Data
- Implementing Matrix Operations
- Accessing an Item from a List
- Adding Items to a List
- Storing Company Employee Table Data Using a List and a Dictionary
- Implementing Set Operations
- Writing and Executing a Script
- Implementing Linear Search
- Implementing Binary Search
- Using Bubble Sort
- Finding the Maximum Number Using Pseudocode
- Checking Whether a Number is Prime
- Finding the Factorial of a Number Using Recursion
- Reading a Text File
- Generating a Density Plot
- Creating a Pie Chart
- Drawing a Scatter Plot to Study the Data
- Visualizing the Titanic Dataset Using a Pie Chart and Bar Plot
- Creating a Class
- Using the init Method
- Implementing Inheritance
- Comparing datetime across Time Zones
- Calculating the Time Delta between Two datetime Objects
- Building a Scorecard Using Dictionary Comprehension and Multiple Lists
- Implementing the __iter__() Method
- Using Regular Expressions to Replace Text
- Using Regular Expressions to Find Winning Customers
- Debugging a Sample Python Code for an Application
- Checking Sample Code with Unit Testing
- Using the Multiprocessing Package
- Using the Argparse Library
- Finding the Mean and Median from a Collection of Income Data
- Using DataFrames to Manipulate Data
- Reading and Viewing the Boston Housing Dataset
- Performing Visual Data Analysis
- Using Machine Learning to Predict Customer Return Rate Accuracy
- Using Linear Regression to Predict the Accuracy of the Median Values of a Dataset
03 / FAQS
Fragen, bevor Sie beginnen
What is a Python Coding Workshop?+
What is the duration of this Workshop?+
Are there any prerequisites for taking this workshop?+
Is this workshop good for my career?+
Does this workshop cover any advanced Python topics?+
Yes, it covers several advanced topics including:
- Regular Expressions
- Functional Programming
- Iterators and Generators
- Debugging and Testing
- Data Science and Machine Learning
Keep going
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Learn Python, from fundamentals to advanced topics.
- 1 Jahr voller Zugang
- 44 LiveLab enthalten
- Abschlusszertifikat
Keine Kreditkarte benötigt