Python With Techctice:


Python is a general-purpose, versatile, and powerful programming language. It’s a great first language because it’s concise and easy to read. Whatever you want to do, Python can do it. From web development to machine learning to data science, Python is the language for you.

Course Description:

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.

Who is a Python Developer?

Though there are many jobs in tech that use Python broadly — including Software Engineer, Web Developer, Data Scientist, and Business Analyst — a dedicated Python Developer will be projected to understand the language at a higher level and be capable of using Python to accomplish any number of tasks, including but not limited to data collection and analytics, database creation, web development, and design, scripting, and automation.

A Python Developer often works in close partnership with data collection and analytics to create useful answers to questions and provide valued insight.

Python is being used in web development, machine learning, AI, scientific computing, and academic research. Its fame can be credited to the rising data science community embracing artificial intelligence and machine learning. Industries like education, healthcare, and finance are using machine-learning applications to innovate their organizations.

Python is also widely used by companies including Netflix, Google, YouTube, Instagram, Facebook, Reddit, and more. Specifically, Spotify uses Python within its back-end services, capturing user data to provide accurate recommendations and playlists. Dropbox, meanwhile, uses Python scripts to create its native applications on each platform (Windows, macOS, Linux, iOS, Android, etc.)

Python Developer Job Description:

  • Have your own GitHub repository built, to function more as your resume
  • Build code that is easily readable, properly documented, and follows key coding standards
  • Read good books on the technology and study peer code that is nicely developed
  • Increase your technology skillset by knowing more about Python libraries
  • Have good knowhow of AI and ML since they go together with Python
  • Take up good freelancing projects with Python, to help build a good experience
  • Contribute to the open source community on platforms like GitHub
  • Have your resume and profile updated to the latest on important platforms
  • Follow online tutorials to help you develop your coding skills

Master Python frameworks, ORM libraries, front-end technologies, and version control

Since Python is so versatile and has so many applications, the best tools for Python Developers to use can be divided into several categories:

Scikit-Learn is an open-source tool that Python Developers, Machine Learning Engineers, and Data Scientists all swear by for data mining and data analysis. Written in Python, Keras is a high-level neural network library that is easy to use and well-suited to machine learning and deep learning. Theano is a Python library useful for evaluating math computations that integrate tightly with NumPy. And SciPy is used for technical and scientific computing.

Selenium is beloved for good reason, as it allows a Python Developer to write scripts in many other languages, including C#, PHP, Perl, Ruby, and Java. Selenium also allows you to perform tests from any browser in all three major operating systems. Robot Framework is also open-source, a generic test automation framework designed for acceptance testing that works not just for web apps, but also for iOS and Android test automation. Like Robot Framework, TestComplete is an automation testing software, but it requires a commercial license.

LXML is a feature-rich, Python-based tool for C libraries. Beautiful Soup is a time-saving Python library that is used for projects like screen-scraping. And Scrapy is an open-source framework written in Python that crawls web pages and extracts data from them.

Though the specific responsibilities will vary, these are some of the basic skills any will need to become a Python Developer:

A Python Developer needs to have a mastery of Python that extends beyond other colleagues in data science, web development, or other fields who might also be expected to have some familiarity with it. A Python Developer must learn object-oriented programming, basic Python syntax, semantics, primitive data types, and arithmetic operators.

One of the major selling points of Python is the massive range of libraries available. A Python Developer should be well-versed in what’s out there and use available libraries to their fullest advantage. Begin by exploring the Python Package Index (PyPi) and becoming familiar with common libraries like Pandas and NumPy.

A Python Developer needs to be knowledgeable about the available frameworks that can be massively helpful depending on the task, including Django, Flask, CherryPy, web2py, TurboGears, and Grok.

Object Relational Mapper (ORM) libraries – examples include SQLAlchemy or Django ORM – help a Python Developer write Python code instead of SQL to create and alter data and schemas in their database.

The skills listed on your Python resume should match what is listed in the job description. The most obvious skill you need is expertise in Python, but other technical skills will vary depending on the role e.g. Senior Python Developer. Because you are submitting a tailored resume, your skills section should reflect what the company needs.

  • Python
  • Degree in computer science
  • Problem-solving
  • Web Frameworks (Django, Flask, Tornado)
  • Object-relational mapper libraries
  • Artificial Intelligence and machine learning domains
  • Deep learning fundamentals
  • Data science fundamentals
  • Data protection fundamentals
  • Testing and debugging
  • Multi-process architecture
  • Version control
  • Git
  • AWS
  • Azure
  • Linux
  • MySQL
  • MongoDB
  • PostgreSQL
  • Apache
  • Bash Scripting
  • OpenCV
  • Machine learning
  • Numpy
  • SciPy
  • Front-end frameworks (Angular, React, Knockout)
  • Unit testing
  • SQL
  • JavaScript
  • C Python
  • Shell scripting
  • Object-oriented programming
  • Experience with big data
  • Test-driven development (TDD)

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    Professional Product Owner Course :

    Build Visions and Inspire Team

    Being a professional Product Owner encompasses more than writing requirements or managing a Product Backlog. Product Owners need to have a concrete understanding of all product management aspects, including but not limited to product ownership, that drives value from their products.

    Who Should Attend

    The Professional Scrum Product Owner course may be interesting to all involved in product development upon the Scrum framework, but has been specifically conceived for those responsible over products from a business and product management perspective and taking up the highly accountable role of Scrum Product Owner. No pre-existing knowledge of Scrum is required to attend.

    Course Objectives

    • Have a clear understanding of the mechanics of Scrum
    • Know how the Product Owner fits into Scrum
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    Python Course Content

    • Introduction to Python
    • Installation of IDE Juypter
    • Understanding first program/script in Python
      • Introduction to data handling
      • Datatypes in Python
        • Numbers
        • Strings
        • Lists
        • Tuples
        • Set
        • Dictionary
      • Operators in Python
        • Arithmetic
        • Relational
        • Identity
        • Logical
        • Bitwise
        • Operator Precedence
      • Expressions
        • Evaluating Expressions
        • Type Casting
      • Python Standard Modules
        • Math Module
        • Random Module
        • Statistics Module
      • Debugging
        • Errors in Python
        • Debugging using Code Tracing
        • Handling Exceptions
    • Introduction
    • Types of statements in Python
    • Understanding IF statements in Python
      • If
      • If else
      • If else if
      • Nested if statement
    • Range () function
    • Iteration/Looping Statements
      • For loop
      • While loop
      • Loop else statement
      • Jump statements
        • Break
        • Continue
      • Loop else statement
      • Nested loops
    • Understanding Strings
    • Creating and accessing the data structure
      • List
      • Tuple
      • Dictionary
    • String Operations
    • String slices
    • String functions and methods
    • List operations
    • Joining
    • Replicating
    • Slicing
      • Working with List
      • Append
      • Insert
      • Updating
      • Delete
      • Sorting
    • Working with Dictionaries
      • Adding elements
      • Updating
      • Deleting
      • Checking for elements
    • Dictionaries Functions and Methods
    • Tuples Operations
    • Tuple Functions and Methods
    • Understanding Sorting
    • Bubble Sort
    • Insertion Sort
    • Classes in Python
    • Working with objects
    • Practical Exercises
    • Functions
    • Defining Functions
    • Passing parameters
    • Return values from functions
    • Scope of variables
    • Introduction
    • Importing modules
    • Working with modules
    • Creating your own python library

    15+ Python Programs for practice

    • Opening, Closing files
    • Working with files
    • Working with CSV files
    • Working with JSON files
    • Hangman Project
    • Rock, paper, scissors
    • Alarm clock with GUI
    • Convert text to speech in python
    • Mad Libs Generator game