Code -
x = 1
while x <= 10:
if x % 3 == 0:
print(x)
x += 1
Python Coding October 31, 2023 Python No comments
x = 1
while x <= 10:
if x % 3 == 0:
print(x)
x += 1
Python Coding October 30, 2023 Python No comments
x = 10
while x > 0:
print(x)
x -= 1
Python Coding October 30, 2023 Course No comments
In this course, you will:
a) understand the basic concepts of machine learning.
b) understand a typical memory-based method, the K nearest neighbor method.
c) understand linear regression.
d) understand model analysis.
Please make sure that you’re comfortable programming in Python and have a basic knowledge of mathematics including matrix multiplications, and conditional probability.
Python Coding October 30, 2023 HTML&CSS, Java No comments
In this project, you’ll support a European travel agency’s effort to increase booking by building a webpage that provides visitors with a 7-day weather forecast for major European cities.
Accomplishing this task will require you to retrieve real-time weather data from an external service. In creating the webpage, you’ll request, process, and present the weather data using HTML, JavaScript, and JSON.
There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers.
ROLE: Software Developer
SKILLS: Web Design, Web Development, Cloud API
PREREQUISITES:
Function closures, asynchronous processing, REST API, and JSON handling with JavaScript
Present content with HTML tags
Present content using classes with CSS
Format and syntax of JSON
Python Coding October 30, 2023 Course, Python No comments
There are 12 modules in this course
This course is an introduction to computer science and programming in Python. Upon successful completion of this course, you will be able to:
1. Take a new computational problem and solve it, using several problem solving techniques including abstraction and problem decomposition.
2. Follow a design creation process that includes: descriptions, test plans, and algorithms.
3. Code, test, and debug a program in Python, based on your design.
Important computer science concepts such as problem solving (computational thinking), problem decomposition, algorithms, abstraction, and software quality are emphasized throughout.
This course uses problem-based learning. The Python programming language and video games are used to demonstrate computer science concepts in a concrete and fun manner. The instructional videos present Python using a conceptual framework that can be used to understand any programming language. This framework is based on several general programming language concepts that you will learn during the course including: lexics, syntax, and semantics.
Other approaches to programming may be quicker, but are more focused on a single programming language, or on a few of the simplest aspects of programming languages. The approach used in this course may take more time, but you will gain a deeper understanding of programming languages. After completing the course, in addition to learning Python programming, you will be able to apply the knowledge and skills you acquired to: non-game problems, other programming languages, and other computer science courses.
You do not need any previous programming, Python, or video game experience. However, several basic skills are needed: computer use (e.g., mouse, keyboard, document editing), elementary mathematics, attention to detail (as with many technical subjects), and a “just give it a try” spirit will be keys to your success. Despite the use of video games for the main programming project, PVG is not about computer games. For each new programming concept, PVG uses non-game examples to provide a basic understanding of computational principles, before applying these programming concepts to video games.
The interactive learning objects (ILO) of the course provide automatic, context-specific guidance and feedback, like a virtual teaching assistant, as you develop problem descriptions, functional test plans, and algorithms. The course forums are supported by knowledgeable University of Alberta personnel, to help you succeed.
All videos, assessments, and ILOs are available free of charge. There is an optional Coursera certificate available for a fee.
Python Coding October 29, 2023 Python No comments
roman = {1:'i',2:'ii'}
d,r=roman
print(d,r)
Python Coding October 28, 2023 Course No comments
Master Algorithmic Programming Techniques. Advance your Software Engineering or Data Science Career by Learning Algorithms through Programming and Puzzle Solving. Ace coding interviews by implementing each algorithmic challenge in this Specialization. Apply the newly-learned algorithmic techniques to real-life problems, such as analyzing a huge social network or sequencing a genome of a deadly pathogen.
Play with 50 algorithmic puzzles on your smartphone to develop your algorithmic intuition! Apply algorithmic techniques (greedy algorithms, binary search, dynamic programming, etc.) and data structures (stacks, queues, trees, graphs, etc.) to solve 100 programming challenges that often appear at interviews at high-tech companies. Get an instant feedback on whether your solution is correct.
Apply the newly learned algorithms to solve real-world challenges: navigating in a Big Network or assembling a genome of a deadly pathogen from millions of short substrings of its DNA.
Learn exactly the same material as undergraduate students in “Algorithms 101” at top universities and more! We are excited that students from various parts of the world are now studying our online materials in the Algorithms 101 classes at their universities. Here is a quote from the website of Professor
If you decide to venture beyond Algorithms 101, try to solve more complex programming challenges (flows in networks, linear programming, streaming algorithms, etc.) and complete an equivalent of a graduate course in algorithms!
Computer science legend Donald Knuth once said “I don’t understand things unless I try to program them.” We also believe that the best way to learn an algorithm is to program it. However, many excellent books and online courses on algorithms, that excel in introducing algorithmic ideas, have not yet succeeded in teaching you how to implement algorithms, the crucial computer science skill that you have to master at your next job interview. We tried to fill this gap by forming a diverse team of instructors that includes world-leading experts in theoretical and applied algorithms at UCSD (Daniel Kane, Alexander Kulikov, and Pavel Pevzner) and a former software engineer at Google (Neil Rhodes). This unique combination of skills makes this Specialization different from other excellent MOOCs on algorithms that are all developed by theoretical computer scientists. While these MOOCs focus on theory, our Specialization is a mix of algorithmic theory/practice/applications with software engineering. You will learn algorithms by implementing nearly 100 coding problems in a programming language of your choice. To the best of knowledge, no other online course in Algorithms comes close to offering you a wealth of programming challenges (and puzzles!) that you may face at your next job interview. We invested over 3000 hours into designing our challenges as an alternative to multiple choice questions that you usually find in MOOCs.
Applied Learning Project
The specialization contains two real-world projects: Big Networks and Genome Assembly. You will analyze both road networks and social networks and will learn how to compute the shortest route between New York and San Francisco 1000 times faster than the shortest path algorithms you learn in the standard Algorithms 101 course! Afterwards, you will learn how to assemble genomes from millions of short fragments of DNA and how assembly algorithms fuel recent developments in personalized medicine.
Python Coding October 28, 2023 Python 1 comment
c = 'hello'
print(c.center(10, '1'))
c = 'hello': In this line, you create a variable c and assign the string 'hello' to it.
c.center(10, '1'): This is the main part of the code where you use the center method on the string c.
c is the string 'hello'.
.center(10, '1') is calling the center method on the string c with two arguments:
10 is the total width you want for the resulting string.
'1' is the character you want to use to fill the remaining space on both sides of the centered string.
The center method then centers the string 'hello' within a total width of 10 characters, using the fill character '1' for the remaining space.
print(c.center(10, '1')): This line prints the result of the center method to the console.
Now, let's break down the output:
The specified total width is 10 characters.
The string 'hello' is 5 characters long.
So, there are 10 - 5 = 5 spaces to fill on either side of 'hello'.
The output is: 11hello111
Python Coding October 28, 2023 Course No comments
The basics of a machine learning system
How to deploy a machine learning model to a microcontroller
How to use machine learning to make decisions and predictions in an embedded system
Machine learning (ML) allows us to teach computers to make predictions and decisions based on data and learn from experiences. In recent years, incredible optimizations have been made to machine learning algorithms, software frameworks, and embedded hardware. Thanks to this, running deep neural networks and other complex machine learning algorithms is possible on low-power devices like microcontrollers.
This course will give you a broad overview of how machine learning works, how to train neural networks, and how to deploy those networks to microcontrollers, which is known as embedded machine learning or TinyML. You do not need any prior machine learning knowledge to take this course. Familiarity with Arduino and microcontrollers is advised to understand some topics as well as to tackle the projects. Some math (reading plots, arithmetic, algebra) is also required for quizzes and projects.
We will cover the concepts and vocabulary necessary to understand the fundamentals of machine learning as well as provide demonstrations and projects to give you hands-on experience.
Python Coding October 28, 2023 Course No comments
This course covers the essential information that every serious programmer needs to know about algorithms and data structures, with emphasis on applications and scientific performance analysis of Java implementations. Part I covers elementary data structures, sorting, and searching algorithms. Part II focuses on graph- and string-processing algorithms.
All the features of this course are available for free. It does not offer a certificate upon completion.
Python Coding October 28, 2023 Cybersecurity No comments
Recognize core skills and knowledge needed to become a cybersecurity analyst
Identify how security attacks impact business operations
Explain security ethics
Identify common tools used by cybersecurity analysts
This course is part of the Google Cybersecurity Professional Certificate
When you enroll in this course, you'll also be enrolled in this Professional Certificate.
Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
This is the first course in the Google Cybersecurity Certificate. These courses will equip you with the skills you need to prepare for an entry-level cybersecurity job.
In this course, you will be introduced to the world of cybersecurity through an interactive curriculum developed by Google. You will identify significant events that led to the development of the cybersecurity field, explain the importance of cybersecurity in today's business operations, and explore the job responsibilities and skills of an entry-level cybersecurity analyst.
Google employees who currently work in cybersecurity will guide you through videos, provide hands-on activities and examples that simulate common cybersecurity tasks, and help you build your skills to prepare for jobs.
Learners who complete the eight courses in the Google Cybersecurity Certificate will be equipped to apply for entry-level cybersecurity roles. No previous experience is necessary.
By the end of this course, you will:
- Identify how security attacks impact business operations.
- Explore the job responsibilities and core skills of an entry-level cybersecurity analyst.
- Recognize how past and present attacks on organizations led to the development of the cybersecurity field.
- Learn the CISSP eight security domains.
- Identify security domains, frameworks, and controls.
- Explain security ethics.
- Recognize common tools used by cybersecurity analysts.
Python Coding October 28, 2023 Python No comments
The walrus operator (:=) in Python, introduced in Python 3.8, allows you to both assign a value to a variable and use that value in an expression in a single line. This can lead to more concise and readable code. Here are three common uses of the walrus operator in Python:
The walrus operator is often used to simplify while loops by allowing you to combine the assignment and condition check in a single line. This is particularly useful when you want to read lines from a file until a certain condition is met.
with open('data.txt') as file:
while (line := file.readline().strip()) != 'END':
# Process the line
In this example, the line variable is assigned the value of file.readline().strip() and then immediately checked to see if it's equal to 'END'. The loop continues until the condition is False.
The walrus operator can simplify list comprehensions by allowing you to use the assigned variable within the list comprehension. This is especially useful when you want to filter or transform elements in a list based on a condition.
numbers = [1, 2, 3, 4, 5]
doubled_even_numbers = [x * 2 for x in numbers if (x % 2 == 0)]
Python Coding October 28, 2023 Course, Python No comments
Gain foundational knowledge, practical skills, and a functional understanding of how generative AI works
Dive into the latest research on Gen AI to understand how companies are creating value with cutting-edge technology
Instruction from expert AWS AI practitioners who actively build and deploy AI in business use-cases today
Generative AI
LLMs
large language models
Machine Learning
Python Programming
In Generative AI with Large Language Models (LLMs), you’ll learn the fundamentals of how generative AI works, and how to deploy it in real-world applications.
By taking this course, you'll learn to:
- Deeply understand generative AI, describing the key steps in a typical LLM-based generative AI lifecycle, from data gathering and model selection, to performance evaluation and deployment
- Describe in detail the transformer architecture that powers LLMs, how they’re trained, and how fine-tuning enables LLMs to be adapted to a variety of specific use cases
- Use empirical scaling laws to optimize the model's objective function across dataset size, compute budget, and inference requirements
- Apply state-of-the art training, tuning, inference, tools, and deployment methods to maximize the performance of models within the specific constraints of your project
- Discuss the challenges and opportunities that generative AI creates for businesses after hearing stories from industry researchers and practitioners
Developers who have a good foundational understanding of how LLMs work, as well the best practices behind training and deploying them, will be able to make good decisions for their companies and more quickly build working prototypes. This course will support learners in building practical intuition about how to best utilize this exciting new technology.
This is an intermediate course, so you should have some experience coding in Python to get the most out of it. You should also be familiar with the basics of machine learning, such as supervised and unsupervised learning, loss functions, and splitting data into training, validation, and test sets. If you have taken the Machine Learning Specialization or Deep Learning Specialization from DeepLearning.AI, you’ll be ready to take this course and dive deeper into the fundamentals of generative AI.
Python Coding October 27, 2023 Python No comments
Python Coding October 26, 2023 Python No comments
r = [20, 40, 60, 80]
r[1:4] = []
print(r)
Python Coding October 26, 2023 Data Science No comments
Learn how to use and apply the powerful language of SQL to better communicate and extract data from databases - a must for anyone working in the data science field.
Please Note: Learners who successfully complete this IBM course can earn a skill badge — a detailed, verifiable and digital credential that profiles the knowledge and skills you’ve acquired in this course. Enroll to learn more, complete the course and claim your badge!
Much of the world's data lives in databases. SQL (or Structured Query Language) is a powerful programming language that is used for communicating with and extracting various data types from databases. A working knowledge of databases and SQL is necessary to advance as a data scientist or a machine learning specialist. The purpose of this course is to introduce relational database concepts and help you learn and apply foundational knowledge of the SQL language. It is also intended to get you started with performing SQL access in a data science environment.
The emphasis in this course is on hands-on, practical learning. As such, you will work with real databases, real data science tools, and real-world datasets. You will create a database instance in the cloud. Through a series of hands-on labs, you will practice building and running SQL queries. You will also learn how to access databases from Jupyter notebooks using SQL and Python.
No prior knowledge of databases, SQL, Python, or programming is required.
Learn and apply foundational knowledge of the SQL language
How to create a database in the cloud
How to use string patterns and ranges to query data
How to sort and group data in result sets and by data type
How to analyze data using Python
Python Coding October 25, 2023 Python No comments
a = [1, 2, 3, 4, 5]
print(a[:4].pop())
This code will print 4. Here's what happens:
a[:4] creates a new list slice containing the elements [1, 2, 3, 4].
Then, pop() is called on this new list slice, which removes and returns the last element of the slice, which is 4.
The print() function then displays the value returned by pop(), which is 4.
Python Coding October 25, 2023 Course No comments
There are 10 courses in this program
Python Coding October 24, 2023 Python No comments
k = [2, 1, 0, 3, 0, 2, 1]
print(k.count(k.index(0)))
The given list is k = [2, 1, 0, 3, 0, 2, 1].
k.index(0) finds the index of the first occurrence of the value 0 in the list k. In this case, the first occurrence of 0 is at index 2.
The result of k.index(0) is 2.
k.count(2) counts how many times the value 2 appears in the list k.
In the list k, the value 2 appears twice, at index 0 and index 5.
So, the final result is 2 because the index of the first occurrence of 0 (which is 2) appears twice in the list k.
Python Coding October 24, 2023 Python No comments
Yes, Python developers are in high-demand.
Python software engineers are also among the highest-paid software developers today, earning an average income of $150,000 a year.
The Python language is easy to learn, yet POWERFUL.
YouTube, Dropbox, Google, Instagram, Spotify, Reddit, Netflix, Pinterest - they are all developed using Python.
And most recently, ChatGPT is also written in Python.
Learning Python opens up the possibilities of a whole new career in Data Science.
This book contains only the first 10 chapters (Chapters 1 to 10) of my online Python course as a Udemy instructor.
Python Coding October 24, 2023 Python No comments
Gain hands-on experience and practice using Python to solve real data science challenges
Practice Python coding for modeling, statistics, and storytelling
Utilize popular libraries such as Pandas, numPy, matplotlib, and SKLearn
Run basic machine learning models using Python, evaluate how those models are performing, and apply those models to real-world problems
Build a foundation for the use of Python in machine learning and artificial intelligence, preparing you for future Python study
Every single minute, computers across the world collect millions of gigabytes of data. What can you do to make sense of this mountain of data? How do data scientists use this data for the applications that power our modern world?
Data science is an ever-evolving field, using algorithms and scientific methods to parse complex data sets. Data scientists use a range of programming languages, such as Python and R, to harness and analyze data. This course focuses on using Python in data science. By the end of the course, you’ll have a fundamental understanding of machine learning models and basic concepts around Machine Learning (ML) and Artificial Intelligence (AI).
Using Python, learners will study regression models (Linear, Multilinear, and Polynomial) and classification models (kNN, Logistic), utilizing popular libraries such as sklearn, Pandas, matplotlib, and numPy. The course will cover key concepts of machine learning such as: picking the right complexity, preventing overfitting, regularization, assessing uncertainty, weighing trade-offs, and model evaluation. Participation in this course will build your confidence in using Python, preparing you for more advanced study in Machine Learning (ML) and Artificial Intelligence (AI), and advancement in your career.
Learners must have a minimum baseline of programming knowledge (preferably in Python) and statistics in order to be successful in this course. Python prerequisites can be met with an introductory Python course offered through CS50’s Introduction to Programming with Python, and statistics prerequisites can be met via Fat Chance or with Stat110 offered through HarvardX.
Python Coding October 24, 2023 Python No comments
Here are 10 advanced Python Command Line Interface (CLI) tricks and techniques that can help you save time and effort when working with CLI applications:
Click is a powerful Python library for creating command-line interfaces. It simplifies the process of defining and parsing command-line arguments and options. By using Click, you can create well-structured and user-friendly CLI applications with minimal code.
import click
@click.command()
@click.option('--name', prompt='Your name', help='Your name')
def hello(name):
click.echo(f'Hello, {name}!')
if __name__ == '__main__':
hello()
If your CLI application has multiple subcommands, use the argparse library to define and manage them. Subcommands allow you to organize your CLI tools logically.
The Colorama library makes it easy to add colored text to your CLI application's output. This can help highlight important information and make your tool more user-friendly.
from colorama import Fore, Style
print(f'{Fore.GREEN}Success!{Style.RESET_ALL} Operation completed.')
Use the tqdm library to add progress bars to your CLI applications, especially for time-consuming tasks. It provides a visual indicator of progress.
from tqdm import tqdm
import time
for i in tqdm(range(10)):
time.sleep(1)
The configparser library allows you to read and write configuration files for your CLI application. This is useful for storing settings and user preferences.
Implement robust logging using Python's built-in logging module. It helps you track errors, debug your application, and provide better user feedback.
import logging
logging.basicConfig(filename='myapp.log', level=logging.INFO)
If your CLI application has a menu-driven interface, use libraries like inquirer or prompt_toolkit to create interactive menus for user input.
You can execute shell commands from within your Python CLI application using the subprocess module. This is useful for running external commands and integrating them into your tool.
import subprocess
result = subprocess.run(['ls', '-l'], capture_output=True, text=True)
print(result.stdout)
Use libraries like tabulate or PrettyTable to format data into tables for better presentation, especially when dealing with tabular data in your CLI application.
Make use of Python's unittest or pytest to create unit tests for your CLI application. Proper testing ensures that your code is robust and reliable.
These advanced Python CLI tricks should help you streamline the development and improve the user experience of your command-line applications. Remember to choose the right tools and techniques based on your specific requirements.
Python Coding October 23, 2023 Python No comments
q = [47, 28, 33, 54, 15]
q.reverse()
print(q[:3])
Python Coding October 23, 2023 Python No comments
What Python is and why Python is relevant to automation
How to write short Python scripts to perform automated actions
How to use the basic Python structures: strings, lists, and dictionaries
How to create your own Python objects
This course is designed to teach you the foundations in order to write simple programs in Python using the most common structures. No previous exposure to programming is needed. By the end of this course, you'll understand the benefits of programming in IT roles; be able to write simple programs using Python; figure out how the building blocks of programming fit together; and combine all of this knowledge to solve a complex programming problem.
We'll start off by diving into the basics of writing a computer program. Along the way, you’ll get hands-on experience with programming concepts through interactive exercises and real-world examples. You’ll quickly start to see how computers can perform a multitude of tasks — you just have to write code that tells them what to do.
Python Coding October 23, 2023 Python No comments
Identify text mining approaches needed to identify and extract different kinds of information from health-related text data.
Differentiate how training deep learning models differ from training traditional machine learning models.
In this MOOC, you will be introduced to advanced machine learning and natural language
processing techniques to parse and extract information from unstructured text documents in
healthcare, such as clinical notes, radiology reports, and discharge summaries. Whether you are an aspiring data scientist or an early or mid-career professional in data science or information technology in healthcare, it is critical that you keep up-to-date your skills in information extraction and analysis.
To be successful in this course, you should build on the concepts learned through other intermediate-level MOOC courses and specializations in Data Science offered by the University of Michigan, so you will be able to delve deeper into challenges in recognizing medical entities in health-related documents, extracting clinical information, addressing ambiguity and polysemy to tag them with correct concept types, and develop tools and techniques to analyze new genres of health information.
By the end of this course, you will be able to:
Identify text mining approaches needed to identify and extract different kinds of information from health-related text data
Create an end-to-end NLP pipeline to extract medical concepts from clinical free text using one terminology resource
Differentiate how training deep learning models differ from training traditional machine learning models
Configure a deep neural network model to detect adverse events from drug reviews
List the pros and cons of Deep Learning approaches."
Python Coding October 22, 2023 Python No comments
n = [76, 24]
p = n.copy()
n.pop()
print(p, n)
Python Coding October 22, 2023 Python No comments
Demonstrate your skills to employers, and leverage industry tools to solve real-world challenges
Load, clean, analyze, process, and visualize data using Python and Jupyter Notebooks
Produce an end-to-end exploratory data analysis using Python and Jupyter Notebooks
In this project, you'll serve as a data analyst at an online retail company helping interpret real-world data to help make key business decisions. Your task is to explore and analyze this dataset to gain insights into the store's sales trends, customer behavior, and popular products.
Upon completion, you’ll be able to demonstrate your ability to perform a comprehensive data analysis project that involves critical thinking, extensive data analysis and visualization, and making data-driven business decisions.
There isn’t just one right approach or solution in this scenario, which means you can create a truly unique project that helps you stand out to employers.
ROLE: Data Analyst
SKILLS: Python
PREREQUISITES:
Python, Numpy, Matplotlib or Seaborn, Git, Jupyter Notebook
This project requires you to independently complete the following steps:
Import required libraries
Load and explore the data
Clean the data
Visualize and analyze the data
Python Coding October 22, 2023 Python No comments
import matplotlib.pyplot as plt
# Define the data for the funnel chart
labels = ['Step 1', 'Step 2', 'Step 3', 'Step 4', 'Step 5']
values = [100, 75, 50, 30, 10]
# Calculate the cumulative values for plotting
cumulative_values = [sum(values[:i+1]) for i in range(len(values))]
# Define colors for each segment
colors = ['blue', 'green', 'orange', 'red', 'purple']
# Create the funnel chart
fig, ax = plt.subplots()
for i in range(len(labels)):
ax.fill_betweenx([i, i + 1], 0, cumulative_values[i], step='mid', alpha=0.7, color=colors[i])
ax.set_yticks(range(len(labels)))
ax.set_yticklabels(labels)
ax.set_xlabel('Conversion Rate')
# Add labels to the bars
for i, value in enumerate(cumulative_values):
ax.annotate(str(value), xy=(value, i), xytext=(5, 5), textcoords='offset points')
plt.title('Funnel Chart')
plt.show()
#clcoding.com
Python Coding October 21, 2023 Python No comments
g = [1, 2, 3, 2, 5]
g.remove(2)
print(g)
Python Coding October 21, 2023 Django No comments
Build & deploy rich web applications using Django. Learn the fundamentals of building a full-featured web site using Django
Install and deploy a Django application; build HTML web pages styled by CSS
Describe and build a data model in Django, applying model query and template tags/code of Django Template Language
Apply built-in login functionality in Django; define sessions, cookies, and one-to-many models
Build objects and write syntactically correct JavaScript language; explain basic elements of low-level jQuery
Learn in-demand skills from university and industry experts
Master a subject or tool with hands-on projects
Develop a deep understanding of key concepts
Earn a career certificate from University of Michigan
Python Coding October 21, 2023 Python No comments
Python courses for developers on Coursera. Keep in mind that new courses may have been added since then, so it's a good idea to explore Coursera's website for the most up-to-date options. Here are a few courses that were well-regarded at the time:
"Python for Everybody" by the University of Michigan: This is a beginner-friendly course that covers the fundamentals of Python programming.
"Python 3 Programming" by the University of Michigan: This is a more advanced Python course that delves into topics like data structures and web scraping.
"Google IT Automation with Python" by Google: This specialization covers Python programming and automation, making it suitable for those interested in IT and system administration.
"Applied Data Science with Python" by the University of Michigan: This is a series of courses that covers various aspects of data science using Python, including data visualization, machine learning, and natural language processing.
"Machine Learning" by Stanford University: While not exclusively a Python course, this is a popular choice for those interested in machine learning with Python.
"Django for Everybody" by the University of Michigan: If you're interested in web development with Python, this course covers the Django framework.
"Advanced Machine Learning Specialization" by the National Research University Higher School of Economics: This specialization focuses on more advanced machine learning techniques using Python.
Python Coding October 20, 2023 Python No comments
lis = [10, 20, 30, 40]
for m in lis:
print(m, end=' ')
if m >= 30:
break
Python Coding October 19, 2023 Python No comments
Gain an immersive understanding of the practices and processes used by a junior or associate data analyst in their day-to-day job
Learn key analytical skills (data cleaning, analysis, & visualization) and tools (spreadsheets, SQL, R programming, Tableau)
Understand how to clean and organize data for analysis, and complete analysis and calculations using spreadsheets, SQL and R programming
Learn how to visualize and present data findings in dashboards, presentations and commonly used visualization platforms
Receive professional-level training from Google
Demonstrate your proficiency in portfolio-ready projects
Earn an employer-recognized certificate from Google
Qualify for in-demand job titles: Data Analyst, Junior Data Analyst, Associate Data Analyst
Python Coding October 19, 2023 Python No comments
for x in range(3):
print(x, end=' ')
Python Coding October 19, 2023 Python No comments
Statistics
Lean Six Sigma
Data Analysis
Minitab
Python Coding October 19, 2023 Python No comments
Apply Python, spreadsheets, and BI tooling proficiently to create visually compelling and interactive data visualizations.
Formulate and communicate data-driven insights and narratives through impactful visualizations and data storytelling.
Assess and select the most suitable visualization tools and techniques to address organizational data needs and objectives.
In today's data-driven world, the ability to create compelling visualizations and tell impactful stories with data is a crucial skill. This comprehensive course will guide you through the process of visualization using coding tools with Python, spreadsheets, and BI (Business Intelligence) tooling. Whether you are a data analyst, a business professional, or an aspiring data storyteller, this course will provide you with the knowledge and best practices to excel in the art of visual storytelling.
Throughout the course, a consistent dataset will be used for exercises, enabling you to focus on mastering the visualization tools rather than getting caught up in the intricacies of the data. The emphasis is on practical application, allowing you to learn and practice the tools in a real-world context. To fully leverage the Python sections of this course, prior experience programming in Python is recommended. Additionally, a solid understanding of high-school level math is expected. Familiarity with the Pandas library will also be beneficial.
By the end of this course, you will possess the necessary skills to become a proficient data storyteller and visual communicator. With the ability to create compelling visualizations and leverage the appropriate tools, you will be well-equipped to navigate the world of data and make informed decisions that drive meaningful impact.
Python Coding October 18, 2023 Python No comments
You define a variable a and set it to the value 10.
a = 10
You have a while loop. The condition for this loop is a > 8, which means the loop will continue executing as long as a is greater than 8.
In the first iteration of the loop, a is indeed greater than 8 (it's 10), so the loop's code block will be executed.
Inside the loop, you print the current value of a using the print function. The end=' ' argument ensures that the values are printed with a space between them.
print(a, end=' ')
After printing the value of a, you decrement a by 1 using the expression a = a - 1. This reduces the value of a by 1 in each iteration, effectively counting down.
a = a - 1
The loop then returns to the condition a > 8. If the condition is still true (which it is as long as a is greater than 8), the loop continues to the next iteration. Steps 3 to 5 are repeated.
This process repeats until a is no longer greater than 8. When a becomes 8, the condition a > 8 is no longer true, and the loop terminates.
The output of this code will be the numbers from 10 down to 9, each separated by a space:
10 9
Once a reaches 8, the loop stops, and the program continues with any code that follows this loop.
Python Coding October 18, 2023 Python No comments
An introduction to computer science as a tool to solve real-world analytical problems using Python 3.5.
Python Coding October 17, 2023 Python No comments
A step-by-step explanation of the code:
for i in range(1):
print(i, end=' ')
Python Coding October 17, 2023 Python No comments
Python is a general-purpose programming language that is becoming ever more popular for data science. Companies worldwide are using Python to harvest insights from their data and gain a competitive edge. Unlike other Python tutorials, this course focuses on Python specifically for data science. In our Introduction to Python course, you’ll learn about powerful ways to store and manipulate data, and helpful data science tools to begin conducting your own analyses. Start DataCamp’s online Python curriculum now.
An introduction to the basic concepts of Python. Learn how to use Python interactively and by using a script. Create your first variables and acquaint yourself with Python's basic data types.
Python Coding October 16, 2023 Python No comments
Python Coding October 16, 2023 Python No comments
Data science courses contain math—no avoiding that! This course is designed to teach learners the basic math you will need in order to be successful in almost any data science math course and was created for learners who have basic math skills but may not have taken algebra or pre-calculus. Data Science Math Skills introduces the core math that data science is built upon, with no extra complexity, introducing unfamiliar ideas and math symbols one-at-a-time.
Learners who complete this course will master the vocabulary, notation, concepts, and algebra rules that all data scientists must know before moving on to more advanced material.
Topics include:
~Set theory, including Venn diagrams
~Properties of the real number line
~Interval notation and algebra with inequalities
~Uses for summation and Sigma notation
~Math on the Cartesian (x,y) plane, slope and distance formulas
~Graphing and describing functions and their inverses on the x-y plane,
~The concept of instantaneous rate of change and tangent lines to a curve
~Exponents, logarithms, and the natural log function.
~Probability theory, including Bayes’ theorem.
While this course is intended as a general introduction to the math skills needed for data science, it can be considered a prerequisite for learners interested in the course, "Mastering Data Analysis in Excel," which is part of the Excel to MySQL Data Science Specialization. Learners who master Data Science Math Skills will be fully prepared for success with the more advanced math concepts introduced in "Mastering Data Analysis in Excel."
Good luck and we hope you enjoy the course!
Python Coding October 15, 2023 Python No comments
This Python code will iterate over the list lis using a for loop. Within each iteration, it will unpack the sublists into the variables p and q. Then it will print the sum of p and q followed by an ampersand (&). Let's go through the steps:
p and q will take the values from the sublists in lis successively.
In the first iteration, p will be 8 and q will be 7. The sum will be 15. So, it will print 15&.
In the second iteration, p will be 6 and q will be 5. The sum will be 11. So, it will print 11&.
Therefore, the output of the code will be: 15&11&
Python Coding October 15, 2023 Books, Python No comments
(2nd Edition: Covers Object Oriented Programming) Learn Python Fast and Learn It Well. Master Python Programming with a unique Hands-On Project
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