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EMTK0001

Mastering Python Programming: A Comprehensive Intermediate’s Guide

Excelators > Global Campus > Mastering Python Programming: A Comprehensive Intermediate’s Guide
Course ID
EMTK0001
Campus
Global Campus
Instructor
Mohammad Kashif
Method
Instructor Led
Pre-Requisites
EMTK0100
Fee
60,000

Description

Unlock a world of opportunities by mastering Python programming with this comprehensive beginner’s course. Whether you’re aiming to land your first Python programming job, advance to a senior software developer position, delve into Machine Learning, Data Science, Django, or simply create your Python apps efficiently, this course equips you with essential skills at an accelerated pace.

Designed for complete beginners and existing programmers seeking to broaden their career prospects, this course ensures a solid foundation in Python programming. Python, a globally popular language, is employed by major companies like Google for mission-critical applications.

  • Requirements
    • ● A computer (Windows, Mac, Linux – all supported)
    • ● Enthusiasm to learn Python, a versatile programming language.
    • ● Module 1 is completed.
  • Key Highlights
    • ● Various modules provide flexible learning pace and sequential skill development for enhanced knowledge retention.
    • ● Build a foundation to confidently apply for Python programming jobs, even with no prior programming experience.
    • ● Learn from real-world examples and industry best practices.
    • ● Taught by instructors with a combined 70 years of professional programming experience, having worked with renowned companies like IBM, Mitsubishi, Fujitsu, and Saab.
    • ● Covers Python 3 with insights into Python 2 for versatility.
    • ● Gain expertise in essential Python keywords, operators, statements, and expressions.
    • ● Comprehensive chapters on object-oriented programming, tKInter (GUI Interfaces), and database usage in Python.
    • ● Utilize powerful Integrated Development Environments (IDEs) like IntelliJ IDEA or PyCharm.
  • Who Should Enroll
    • ● Beginners with no prior programming experience seeking their first programming job.
    • ● Individuals aspiring to enter machine learning, data science, or artificial intelligence fields.
    • ● Existing programmers aiming to boost career options by mastering Python.
    • ● Not suitable for expert Python programmers with extensive knowledge and many years of experience.

Course Outline

*Please ensure Level 0 is completed

  • Functions
    • ● Defining a function
    • ● Program flow when calling a function.
    • ● Parameters and arguments
    • ● Debugging with parameters
    • ● Palindromes
    • ● Palindrome challenge solution
    • ● Sentence challenge solution
    • ● Functions calling functions.
    • ● Returning values
    • ● Get_integer Challenge solution.
    • ● Returning None
    • ● Functions that perform actions
    • ● Handling invalid arguments
    • ● Width challenge solution
    • ● Default parameter values
    • ● Keyword arguments
    • ● Docstrings
    • ● Writing a Docstring
    • ● How professional is that!
    • ● Solution to Docstrings challenge
    • ● Fibonacci Numbers
    • ● Writing a fibonacci function
    • ● Function annotations and type hints
    • ● Function annotations with default values
    • ● Solution to banner_text Docstring challenge
    • ● A history lesson.
    • ● Printing in color
    • ● Running your program like a user
    • ● Windows Only - Installing pre-release version of colorama
    • ● colorama module and virtual environments
    • ● Activating a virtual environment
    • ● A function to test our HiLo game.
    • ● Counting correct guesses
    • ● *args
    • ● colour_print with multiple arguments
    • ● Rules for variable number of arguments
    • ● Defining different parameter types
  • Dictionaries and Sets
    • ● What is a dictionary?
    • ● Iterating over a dictionary
    • ● Adding items to a dictionary
    • ● Changing values in a dictionary
    • ● Removing items from a dictionary
    • ● Using `in` with a dictionary
    • ● Dictionary menu challenge solution
    • ● Using a list with a dictionary
    • ● Adding items to a dictionary
    • ● Smart fridge
    • ● What's for tea?
    • ● Using several dictionaries together
    • ● Checking the pantry
    • ● Checking quantities - choosing a data structure
    • ● Checking quantities - the code
    • ● Solution: Create a shopping list challenge
    • ● The setdefault method
    • ● APIs and a mobile phone demo
    • ● The `dict` documentation
    • ● The remaining `dict` methods
    • ● The dict `update` method
    • ● The dict `values` method
    • ● References to mutable objects
    • ● Shallow copy, step-by-step
    • ● Deep copy
    • ● Simple deep copy solution
    • ● Hash functions
    • ● A bad hashing function
    • ● Hash tables
    • ● Completing our simple dictionary implementation
    • ● Hash functions and security
    • ● Hashlib, the secure hash module
    • ● Introduction to Android-Tim
    • ● Introduction to sets
    • ● Python sets
    • ● Implications of sets being unordered
    • ● Set membership.
    • ● Testing set membership is fast.
    • ● Adding items to a set
    • ● Using a set to remove duplicate values.
    • ● Deleting items from a set
    • ● The `discard` method
    • ● The `remove` method.
    • ● The `pop` method
    • ● Set union.
    • ● Set union in practice.
    • ● Union update
    • ● Advantage of the set operation methods over the operators
    • ● Set intersection, Set difference.
    • ● Set symmetric difference.
    • ● Subsets and supersets
    • ● Subsets and supersets in Python
    • ● Practical application of subsets and supersets
  • Reading and Writing Files in Python
    • ● Files and directories
    • ● Introduction to the command prompt or terminal
    • ● Paths
    • ● Text files
    • ● Reading from a text file
    • ● Opening a file using `with`
    • ● Read, readline and readlines
    • ● Strip, lstrip and rstrip
    • ● Removeprefix and removesuffix in Python 3.9
    • ● Parsing data in a text file
    • ● Working with text data
    • ● Solution to capital city challenge
    • ● Dictionary values with multiple keys
    • ● Printing data to a text file
    • ● Writing data to a text file
    • ● File modes
    • ● Unicode – a brief history
    • ● Unicode in Python
    • ● File encodings
    • ● Serializing data using JSON
    • ● Limitations of JSON
    • ● Practical application - parsing JSON data
    • ● Practical application - parsing JSON data from the internet
    • ● The CSV format.
    • ● Reading a CSV file
    • ● Quoting in a CSV file
    • ● Sniffer and Dialect
    • ● CSV Dialect
    • ● Writing a CSV file
    • ● The csv DictReader
    • ● Solution to DictReader challenge
    • ● Field names with DictReader and DictWriter
    • ● Reading and writing multiple files
    • ● The csv DictWriter
    • ● The `zip` function
    • ● Reading and writing to the same text file
    • ● Solution to parsing functions challenge
    • ● The record_invoice function
    • ● Using the `record_invoice` function
    • ● Seek and tell
    • ● Improving the `record_invoice` function
    • ● Summary of working with text files
    • ● Working with binary files - bytes and bytearray
    • ● Reading a bitmap file
    • ● Little endian and big endian
    • ● Making sense of binary data
    • ● Reading tags in an mp3 file
    • ● The ID3v2 specification
    • ● Filling in the blanks
    • ● Extracting images
    • ● Testing our read_id3 program
    • ● Checking the hash of a file
  • Modules and Functions
    • ● Modules and Functions in Python
    • ● Modules and import
    • ● The standard Python library
    • ● WebBrowser Module
    • ● Time and DateTime in Python
    • ● Preview
    • ● Timezones
    • ● Check Path In Windows
    • ● Check Path on a Mac
    • ● Installing the pytz module (Windows/Mac/Linux)
    • ● Introduction to Tkinter
    • ● TkInter - Pack Geometry Manager
    • ● TkInter - Grid Geometry Manager
    • ● Functions in Python
    • ● Parabola - More on Functions
    • ● Scope in Functions
    • ● Fix Function and Draw Circles
    • ● Load Cards
    • ● Deal Cards
    • ● Global Variables
    • ● Global Keyword
    • ● Test Blackjack Game
    • ● Blackjack Challenge
    • ● Importing Techniques
    • ● Underscores in Python code
    • ● Namespaces, more on Scope and Recursion
    • ● Recursion with OS Module and Filesystem and Nonlocal keyword
    • ● Nonlocal keyword, Free and LEGB
  • Object Oriented Python
    • ● Object Orientated Programming and Classes
    • ● Instances, Constructors, Self and more
    • ● Class Attributes
    • ● Non Public and Mangling
    • ● DocStrings and Raw Literals
    • ● Album class and More on DocStrings
    • ● Artist class and import Albums.
    • ● Load data and Write Checkfile
    • ● Implement Revised Load_Data Algorithm
    • ● Write OOP Version
    • ● Getters and Properties
    • ● Remove Circular References Challenge
    • ● Getters and Setters
    • ● Data Attributes and Properties
    • ● Alternate Syntax for Properties
    • ● Inheritance
    • ● Subclasses and Overloading
    • ● Calling Super Methods
    • ● Changing Behavior of Methods
    • ● Overriding Methods
    • ● Inheritance Challenge
    • ● Polymorphism
    • ● Composition
    • ● Composition Continued
  • Databases in Python
    • ● Using Database in Python
    • ● Database Terminology
    • ● Sqlite3 Install
    • ● Introduction to SQLite
    • ● More with SQL using SQLite.
    • ● Order by and Joins
    • ● More complex Joins
    • ● Wildcards and Views
    • ● Housekeeping and the Challenge
    • ● SQL in Python
    • ● Connections, Cursors and Transactions
    • ● SQL Injection Attacks
    • ● Placeholders and Parameter Substitution
    • ● Exceptions
    • ● Exceptions Challenge
    • ● Exceptions Continued
    • ● Raising Exceptions
    • ● More on Exceptions
    • ● Exceptions and TODO
    • ● Rolling back Transactions
    • ● Adding Database code to the Account Class
    • ● GUI Database Editing Overview
    • ● Ultimate Edition Database View
    • ● Problems with Community Edition database plugin
    • ● Update Deposit and Withdrawal Methods
    • ● Displaying Time in Different Timezones
    • ● SQLite3 strftime Function
    • ● Problems Storing Timezones
    • ● Rolling Back Transactions
    • ● Simple Database Browser
    • ● Scrollbars
    • ● Star Args
    • ● Kwargs
    • ● Scrollable Listbox
    • ● Populating a Listbox from a Database
    • ● The DataListbox Class Code
    • ● Linking our DataListBoxes
  • Generators, Comprehensions and the timeit
    • ● Generators and Yield
    • ● Next and Ranges
    • ● Generator Examples - Fibonacci numbers and Calculating Pi
    • ● The os.walk Generator
    • ● Searching the Filesystem
    • ● Reading Mp3 Tags
    • ● List Comprehensions
    • ● Challenge Solutions
    • ● Conditional Comprehensions
    • ● Conditional Expressions
    • ● Challenges
    • ● Nested Comprehensions
    • ● The timeit Module
    • ● Map Intro
    • ● Map Challenge Completion
    • ● The Filter Function
    • ● The Reduce Function
    • ● any and all
    • ● Named Tuples
    • ● any and all with Comprehensions
    • ● Lambda expressions
    • ● Conditional expressions
    • ● Conditional expression challenge
    • ● A lambda with a conditional expression
    • ● A toy calculator
    • ● A lambda in a loop
    • ● Methods of some state-carrying object
    • ● Frame makes a good base class
    • ● `eval` is dangerous!
    • ● Control all input to `eval`
    • ● Mitigating the danger of `eval`
    • ● Functions are objects
  • Big O Notation
    • ● Big O tables and graphs
    • ● Bubble sort
    • ● Big O of Bubble sort, and an optimisation
    • ● Big O of our improved Bubble sort
    • ● Bubble sort optimisation
    • ● Best, worst and average cases
    • ● Big O summary
Duration Place Mode Focus Instructor
48 Hours (2-Months) Excelators Instructor Led Mastering Python Mohammad Kashif

Why Choose This Course

This isn’t just a course; it’s a whole university degree condensed into one incredibly affordable package. Get ready for a highly practical learning experience right from the first class.

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