Django Coder At the top! – Django Coder Steps!
Django Developer Steps! – Django Developer Success!
Python Programmer Simple as ABC! – Python Programmer Trustworthy!
A complete practical Python Tutorial for both beginners & intermediates! Master Python 3 by making 10 amazing Python apps.
- Go from a total beginner to a confident Python programmer
- Create 10 real-world Python programs (no toy programs)
- Strengthen your skills with bonus practice activities throughout the Tutorial
- Create an English Thesaurus app that returns definitions of English words
- Create a personal website entirely in Python
- Create a mobile app that improves your mood
- Create a portfolio website and publish it on a real server
- Create a desktop app for storing data for books
- Create a webcam app that detects moving objects
- Create a web scraper that extracts real-estate data
- Create a data visualization app
- Create a database app
- Create a geocoding web app
- Send automated emails
- Analyze and visualize data
- Use Python to schedule programs based on computer events.
- Learn OOP (Object-Oriented Programming)
- Learn GUIs (Graphical-User Interfaces)
- A computer (Windows, Mac, or Linux).
- No prior knowledge of Python is required.
- No previous programming experience needed.
The Python Programmer Tutorial is the most practical Tutorial you will find on the web today. In this Tutorial, rather than practicing rote memorization, The purpose of this Tutorial is to get you from zero and help you become a Python Programmer. We will achieve that by building actual desktop programs, developing interactive web applications, automating tasks, and even creating mobile apps entirely in Python 3.
Python Programmer In record time! – The Efficient Python Programmer
You will learn the entire process of program development in Python, from writing a program to producing the final .exe or .app executable which you can share with friends and colleagues.There will be 10 real-world applications that we will build together. These are:
- English Thesaurus – a program where users can get definitions of words.
- Volcano Web Map – an interactive web map of volcano locations throughout the USA.
- Personal Website with Python – a live website built entirely in Python.
- Bookshop Database App – a desktop GUI app with an SQL database backend.
- Feel Good Mobile App – an Android & iOS app.
- Webcam Motion Detector – starts the webcam and detects moving objects.
- Real Estate Web Scraper – a program that extracts data from webpages.
- Interactive Data Dashboard – a web-based, fully interactive graph.
- Database Web App – a web app that collects data & sends emails.
- Geocoder Web App – a web app that converts addresses to coordinates.
Before we start building the apps, you will first learn the fundamentals of Python programming. If you know Python basics already, you can jump right in with the first app. By building the apps, you will master Python and gain the skills to create Python programs independently. You can also use any of the 10 apps for your portfolio.
You will code the apps, guided step-by-step by straightforward video explanations.
To consider yourself a professional python programmer, you need to know how to write professional programs. There’s no other course that teaches you that, so join thousands of other students who have successfully applied their Python skills in the real world. Sign up and start learning the fantastic Python programming language today!
Who this course is for:
- Those with no prior knowledge of Python.
- Those who know Python basics and want to master Python
This Specialization builds on the success of the Python for tutorial and will introduce fundamental programming concepts including data structures, networked application program interfaces, and databases, using the Python programming language. You’ll use the technologies learned throughout the Specialization to design and create your own applications for data retrieval, processing, and visualization. Become Freelance Python Programmer..
Python Data Science Guide! – Python Data Science Straightforward!
A complete data science case study: preprocessing, modeling, model validation and maintenance in Python
- Improve your Python modeling skills
- Differentiate your data science portfolio with a hot topic
- Fill up your resume with in demand data science skills
- Build a complete credit risk model in Python
- Impress interviewers by showing practical knowledge
- How to preprocess real data in Python
- Learn credit risk modeling theory
- Apply state of the art data science techniques
- Solve a real-life data science task
- Be able to evaluate the effectiveness of your model
- Perform linear and logistic regressions in Python
- No prior experience is required. We will start from the very basics
- You’ll need to install Anaconda and Python. We will show you how to do that step by step
Hi! Welcome to Python Credit Risk Modeling. A tutorial that teaches you how banks use python data science modeling to improve their performance and comply with regulatory requirements. This is the perfect tutorial for you, if you are interested in a python data science career.
· The tutorial is suitable for beginners. We start with theory, initial data and gradually solve a complete in front of you
· Everything we cover is up-to-date and relevant in today’s development of Python models for the banking industry
· It shows the complete picture in credit risk in Python (using state of the art techniques to model all three aspects of the expected loss equation – PD, LGD, and EAD) including creating a scorecard from scratch
· Here we show you how to create models that are compliant with Basel II and Basel III regulations that other courses rarely touch upon
· We are not going to work with fake data. The datasets used in this tutorial is an actual real-world example
· You get to differentiate your python data science portfolio by showing skills that are highly demanded in the job marketplace
· What is most important – you get to see first-hand how a python data science task is solved in the real-world
Most python data science tutorials cover several frameworks, and theoretical part. This is like learning how to taste wine before being able to open a bottle of wine.
Our goal is to help you build a solid foundation. We want you to study the theory, learn how to pre-process data that does not necessarily come in the “friendliest” format, and of course, only then we will show you how to build a state of the art model and how to evaluate its effectiveness.
- Weight of evidence
- Information value
- Fine classing
- Coarse classing
- Linear regression
- Logistic regression
- Area Under the Curve
- Receiver Operating Characteristic Curve
- Gini Coefficient
- Assessing Population Stability
- Maintaining a model
Make sure that you take full advantage of this amazing opportunity!
Who this tutorial is for:
- You should take this tutorial if you are a data science student interested in improving their skills
- You should take this tutorial if you want to specialize in credit risk modeling
- The tutorial is also ideal for beginners, as it starts from the fundamentals and gradually builds up your skills
- This tutorial is for you if you want a great career
Hi I’m Al Ardosa the Fellow Actuary. I’ve been making tutorials since 2013. I’m here to help you do the same. I’ve majored in Computer Science and do advanced studying methods. My purpose is to make sure you understand every concept in these tutorials. If you get stuck with anything, send me a message, I’m here to help.
I’ve been working as a senior software developer and tech lead in Lazada and other tech companies for many years, and is now taking all that I’ve learned, to teach programming skills and to help you discover the amazing career opportunities that being a developer.
Python Finance Data Analysis Excited Roadmap!
-Codes in Python
-Career to the next level
-Conditional statements, functions, sequences, and loops
-Solve real-world tasks
Get a job as a data scientist with Python
Acquire solid financial acumen
Carry out in-depth investment analysis
Build investment portfolios
Calculate risk and return of individual securities
Calculate risk and return of investment portfolios
Apply best practices when working with financial data
Use univariate and multivariate regression analysis
Understand the Capital Asset Pricing Model
Compare securities in terms of their Sharpe ratio
Perform Monte Carlo simulations
Learn how to price options by applying the Black Scholes formula
Be comfortable applying for a developer job in a financial institution
Learn how to use Python in a working environment?
Are you a young professional interested in a career in Data Science?
Would you like to explore how Python can be applied in the world of Finance and solve portfolio optimization problems?
If so, then this is the right course for you!
We are proud to present Python for Finance: Investment Fundamentals and Data Analytics – one of the most interesting and complete courses we have created so far. It took our team slightly over four months to create this course, but now, it is ready and waiting for you.
An exciting journey from Beginner to Pro.
If you are a complete beginner and you know nothing about coding, don’t worry! We start from the very basics. The first part of the course is ideal for beginners and people who want to brush up on their Python skills. And then, once we have covered the basics, we will be ready to tackle financial calculations and portfolio optimization tasks.
And it gets even better! The Finance block of this course will teach you in-demand real-world skills employers are looking for. To be a high-paid programmer, you will have to specialize in a particular area of interest. In this course, we will focus on Finance, covering many tools and techniques used by finance professionals daily:
Rate of return of stocks
Risk of stocks
Rate of return of stock portfolios
Risk of stock portfolios
Correlation between stocks
Diversifiable and non-diversifiable risk
Alpha and Beta coefficients
Measuring a regression’s explanatory power with R^2
Markowitz Efficient frontier calculation
Capital asset pricing model
Multivariate regression analysis
Monte Carlo simulations
Using Monte Carlo in a Corporate Finance context
Derivatives and type of derivatives
Applying the Black Scholes formula
Using Monte Carlo for options pricing
Using Monte Carlo for stock pricing
Everything is included! All these topics are first explained in theory and then applied in practice using Python.
Is there a better way to reinforce what you have learned in the first part of the course?
Even if you are an experienced programmer, as we will teach you a great deal about the finance theory and mechanics you will need if you start working in a finance context.
Teaching is our passion.
Everything we teach is explained in the best way possible. Plain and clear English, relevant examples and time-efficient videos. Don’t forget to check some of our sample videos to see how easy they are to understand.
If you have questions, contact us! We enjoy communicating with our students and take pride in responding within the 1 business day. Our goal is to create high-end materials that are fun, exciting, career-enhancing, and rewarding.
What makes this course different from the rest of the Programming and Finance courses out there?
Teach you how to code in Python and apply these skills in the world of Finance. It is both a Programming and a Finance course.
Just subscribe to this course! If you don’t acquire these skills now, you will miss an opportunity to separate yourself from the others. Don’t risk your future success! Let’s start learning together now!
Who this course is for:
Aspiring data scientists
People interested in finance and investments
Programmers who want to specialize in finance
Everyone who wants to learn how to code and apply their skills in practice
Finance graduates and professionals who need to better apply their knowledge in Python
Automate the Boring Stuff With Python Guilt-free!
-Automate tasks on their computer by writing simple Python programs.
-Write programs that can do text pattern recognition with “regular expressions”.
-Programmatically generate and update Excel spreadsheets.
-Parse PDFs and Word documents.
-Crawl web sites and pull information from online sources.
-Write programs that send out email notifications.
-Use Python’s debugging tools to quickly figure out bugs in your code.
-Programmatically control the mouse and keyboard to click and type for you.
-No programming experience is required.
-Downloading and installing Python is covered at the start of the course.
-Basic computer skills: surfing websites, running programs, saving and opening documents, etc.
If you’re an office worker, student, administrator, or just want to become more productive with your computer, programming will allow you write code that can automate tedious tasks. This course follows the popular (and free!) book, Automate the Boring Stuff with Python.
Automate the Boring Stuff with Python was written for people who want to get up to speed writing small programs that do practical tasks as soon as possible. You don’t need to know sorting algorithms or object-oriented programming, so this course skips all the computer science and concentrates on writing code that gets stuff done.
This course is for complete beginners and covers the popular Python programming language. You’ll learn basic concepts as well as:
-Parsing PDFs and Excel spreadsheets
-Automating the keyboard and mouse
-Sending emails and texts
-And several other practical topics
By the end of this course, you’ll be able to write code that not only dramatically increases your productivity, but also be able to list this fun and creative skill on your resume.
Who is the target audience?
-Office workers, students, small/home business workers, and administrators would want to improve their productivity.
-Aspiring software engineers who want to add skills to their programming vault.
-Computer users who have heard the “learn to code” message, but want practical reasons to learn programming.
-Experienced Python software engineers can skip the first half of the course, but may find the later parts that cover various third-party modules helpful.
-While this course doesn’t cover specific devops tools, this course would be useful for QA, devops, and admins who want to learn scripting in Python.
Python Logistic Regression From Scratch Roadmap!
You can Learn:
-Program logistic regression from scratch in Python
-Describe how logistic regression is useful in data science
-Derive the error and update rule
-Understand how logistic regression works as an analogy for the biological neuron
-Use logistic regression to solve real-world business problems like predicting user actions from e-commerce data and facial expression recognition
-Understand why regularization is used in machine learning
Basics: What is linear classification? What’s the relation to neural networks?
-Solving for the optimal weights
-Project: Facial Expression Recognition
-Effective Learning Strategies for Machine Learning
This is a lead-in to deep learning and neural networks – it covers a popular and fundamental technique used in machine learning, data science and statistics: logistic regression. We cover the theory from the ground up: derivation of the solution, and applications to real-world problems. We show you how one might code their own logistic regression module in Python.
This does not require any external materials. Everything needed (Python, and some Python libraries) can be obtained for free.
This provides you with many practical examples so that you can really see how deep learning can be used on anything. It will show you how to predict user actions on a website given user data like whether or not that user is on a mobile device, the number of products they viewed, how long they stayed on your site, whether or not they are a returning visitor, and what time of day they visited.
Imagine being able to predict someone’s emotions just based on a picture!
If you are a programmer and you want to enhance your coding abilities by learning about data science, then this is for you. If you have a technical or mathematical background, and you want use your skills to make data-driven decisions and optimize your business using scientific principles, then this is for you.
This is focuses on “how to build and understand”, not just “how to use”. Anyone can learn to use an API in 15 minutes after reading some documentation. It’s not about “remembering facts”, it’s about “seeing for yourself” via experimentation. It will teach you how to visualize what’s happening in the model internally. If you want more than just a superficial look at machine learning models, this is for you.
-Adult learners who want to get into the field of data science and big data
-Students who are thinking of pursuing machine learning or data science
-Students who are tired of boring traditional statistics and prewritten functions in R, and want to learn how things really work by implementing them in Python
-People who know some machine learning but want to be able to relate it to artificial intelligence
-People who are interested in bridging the gap between computational neuroscience and machine learning
Hire Python Developer Freelancers Professional! But how?
- Learn to use Python professionally!
- Learn advanced Python features, like the collections module and how to work with timestamps!
- Learn to use Object Oriented Programming with classes!
- Understand complex topics, like decorators.
- Build a complete understanding of Python from the ground up!
Learn Python like a Professional! Start from the basics and go all the way to creating your own applications and games!
- Access to a computer with an internet connection.
Whether you have never programmed before, already know basic syntax, or want to learn about the advanced features of Python.
- Python Comparison Operators
- Python Statements
- Methods and Functions
- Milestone Project
- Object Oriented Programming
- Modules and Packages
- Errors and Exception Handling
- Milestone Project – 2
- Built-in Functions
- Python Decorators
- Python Generators
- Advanced Python Modules
- Advanced Python Objects and Data Structures
- Milestone Project – 3
- Bonus Material – Introduction to GUIs
- Command Line Basics
- Installing Python
- Running Python Code
- Number Data Types
- Print Formatting
- Built-in Functions
- Debugging and Error Handling
- External Modules
- Object Oriented Programming
- File I/O
- Advanced Methods
- Unit Tests
- and much more!
Advance your career and increase your knowledge, all in a fun and practical way!
This is for:
- Beginners who have never programmed before.
- Programmers switching languages to Python.
- Intermediate Python programmers who want to level up their skills!