Course Content
Module 1 – Getting Started with Python
introduced the fundamentals of Python, giving beginners a clear understanding of how the language works and how to start writing simple programs. Python was highlighted as a beginner-friendly language with simple syntax, making it easy to read and write code.
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Module 2 – Introduction to Python Programming
In this Introduction to Python module, learners explore Python’s clear, readable syntax and powerful features. Beginning with installation and a simple “Hello, World!” script, you will progress through variables, control flow and functions using step-by-step examples. By the end, you will be equipped to write your own Python programmes, automate routine tasks and tap into an extensive library ecosystem for real-world projects.
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Basic Command for Command prompt, PowerShell, Zsh(macOS)
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Module 3 – Variables, Data Types and Basic Operations
In the Variables, Data Types and Basic Operations in Python module, learners explore how to store and manage data using variables, master fundamental types such as integers, floats, strings and booleans, and perform arithmetic, comparison and logical operations step by step. Clear explanations, real world examples and hands on exercises guide you through writing and debugging code. By the end of this module, you will be ready to build dynamic Python programs and automate everyday tasks.
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Module 4 – Control Flow – Conditions and Loops
Control flow structures determine the order in which your program’s code executes. With conditional statements, you can make decisions and execute certain code blocks only when specific conditions are met. Loops allow you to repeat actions efficiently without writing redundant code. In this module, we will explore fundamental control flow concepts in Python in a step-by-step manner, similar to Microsoft’s learning curriculum. By the end, you’ll understand how to use if, elif, and else statements (including nested conditions) for decision-making, how truthy and falsy values work in Boolean logic, how to construct for loops (using range() and iterating over collections), how to use while loops along with loop control statements (break and continue), and how to leverage list comprehensions and generator expressions for concise looping. Finally, we’ll apply these concepts in a practical exercise to build an interactive decision-making system. Each section below includes explanations, code examples, and mini-exercises to reinforce the concepts, all formatted for clarity and easy follow-along.
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Day 1 Summary
We covered Modules 1, 2 & Module 3 (Lesson 1 & 2)
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Module 5 – Functions and Code Organisation
Imagine you need to clean up a messy data set or send a personalised email to each customer. Instead of writing the same steps over and over, you can create a function and call it whenever you need. In this lesson on Functions and Code Organisation, you will learn how to define functions, pass and return information, document your work and group related code into modules for easy reuse and maintenance.
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Day 2 Summary
Summary for Day 21 Aug 2025
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Day 3 Summary
Summary of Day 28 Aug 2025
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Module 7 – Working with Files and Folders
In this lesson, we will learn how to manipulate files and directories using Python. We’ll explore common file operations using the os module, and see how the pathlib module provides an object-oriented way to handle file paths. We’ll also use the glob module for pattern-based file searches and learn file I/O operations for text, CSV, and binary files. Additionally, we’ll introduce the calendar and time modules to work with dates and timestamps. Finally, an interactive lab will tie everything together by automating a folder backup and cleanup task. Follow the step-by-step sections below for each subtopic, try out the code examples, and explore the guided lab at the end.
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Module 8 – Error Handling and Debugging Techniques
In this lesson, we will learn how to handle errors in Python programs and how to debug code effectively. Errors are inevitable, but knowing how to manage them ensures our programs don't crash unexpectedly. We will cover the difference between syntax errors and exceptions, how to use try, except, else, and finally blocks to catch and handle exceptions, and how to raise your own exceptions (including creating custom exception classes). We’ll also explore debugging strategies: using simple print statements or the logging module to trace your program’s execution, and using Python’s interactive debugger pdb to step through code. By following best practices for error handling and debugging, you can write resilient, maintainable code. Throughout this lesson, try the examples and exercises to practice these techniques.
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Day 4 Summary
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Module 9 – Automating Excel and PDFs with Python
In this lesson, you will learn how to automate common communication and reporting tasks using Python. We will cover sending notifications via email, messaging platforms, and SMS, as well as manipulating Excel spreadsheets and PDF files programmatically. Each section below includes step-by-step explanations, code examples, and interactive exercises to reinforce your understanding. By the end of this lesson, you’ll be able to send emails with attachments, integrate with Slack/Microsoft Teams, send SMS alerts, and automate Excel/PDF workflows.
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Day 5 Summary
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Mini Project: Build your own Automation Tool
The project incorporates two common automation tasks – Contact Management and Student Tasks Tracking
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Day 6 Summary
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Introduction to Python Programming (Copy 1)

Introduction to the calendar and time Modules for Timestamps

Date and time handling is another important aspect, especially when dealing with file timestamps for backups, logging, or scheduling. Python provides several modules for this, but two basic ones are:

time – low-level time-related functions (timestamps, sleep, etc.).

calendar – functions for calendar dates, such as printing calendars and checking days.

We’ll touch on these to get a current timestamp and to work with calendar dates. (The datetime module is more powerful for date/time arithmetic, but here we focus on time and calendar as per our syllabus.)

Using the time Module

The time module is useful for working with timestamps (points in time) and simple time-related tasks.

Current Time (Timestamp): time.time() returns the current time as a timestamp, which is the number of seconds since the Unix epoch (Jan 1, 1970) in UTC. It returns a float (with sub-second precision). Example:

import time
now_ts = time.time()
print(now_ts)

Output will be a large number like 1754862050.4579918 (your output will vary). This is rarely human-readable, but is useful for calculations (e.g., measure durations) or storing an absolute time.

Convert Timestamp to Structured Time: time.localtime(timestamp) converts a timestamp to a struct_time (a tuple-like object) in local time. If you omit the timestamp, it uses the current time. For example:

current_struct = time.localtime()
print(current_struct.tm_year, current_struct.tm_mon, current_struct.tm_mday)

This might print something like 2025 8 6 for 6th August 2025. The struct_time has attributes like tm_year, tm_mon (month), tm_mday (day of month), tm_hour, tm_min, tm_sec, etc.

Formatted Date/Time Strings: To get a nicely formatted date/time string (timestamp in human-readable form), use time.strftime(format, [t]). The strftime function formats a time tuple (t) according to a format string. If you don’t provide t, it will format the current local time. Format strings use placeholders like %Y for year, %m for month, %d for day, %H for hour (24-hour clock), %M for minute, %S for second, etc.

Example – get the current date/time as a string:

import time
now_str = time.strftime("%Y-%m-%d %H:%M:%S")
print("Current date and time:", now_str)

This might output: Current date and time: 2025-08-06 23:20:45 (depending on when you run it). Here %Y became 2025, %m 08, %d 06, etc., constructing a familiar datetime format.

You can change the format string to many different combinations. For instance, %A for full weekday name, %B for full month name, %I for 12-hour clock hour, %p for AM/PM, and so on. time.strftime is very flexible for creating timestamp strings for filenames or logs.

Pausing Execution: Not directly related to timestamps, but worth knowing: time.sleep(seconds) will pause your script for the given number of seconds. For example, time.sleep(1.5) waits 1.5 seconds. This can be useful in scheduling loops or waiting for a certain time.

Using the calendar Module

The calendar module is handy for tasks related to dates and calendars. It can generate calendars and provide info about days.

Print a Calendar: You can print a text calendar for a month using calendar.month(year, month). This returns a string with a simple text calendar. For example:

import calendar
cal_str = calendar.month(2025, 8)
print(cal_str)

Output:

    August 2025
Mo Tu We Th Fr Sa Su
             1  2  3
 4  5  6  7  8  9 10
11 12 13 14 15 16 17
18 19 20 21 22 23 24
25 26 27 28 29 30 31

This is a nicely formatted calendar for August 2025.

Similarly, calendar.calendar(year) will return a whole year’s calendar as a big string (12 months). There are also calendar.prmonth(year, month) and calendar.prcal(year) that directly print to stdout.

Weekday and Week Information: The function calendar.weekday(year, month, day) returns the day of the week as an integer, where Monday is 0 and Sunday is 6 by default. For example:

day_index = calendar.weekday(2025, 8, 6)
print(day_index)  # 0=Mon, 1=Tue, ..., 6=Sun

For Aug 6, 2025, this will print 2 (if Monday=0, that means Wednesday, since 0->Mon,1->Tue,2->Wed). If you want the name of the day, you can use:

import calendar
days = list(calendar.day_name)  # ['Monday', 'Tuesday', ... 'Sunday']
print(days[day_index])  # e.g., "Wednesday"

The calendar module provides calendar.day_name (an iterable of weekday names) and calendar.month_name for month names if needed.

Useful Calendar Functions:

  • calendar.isleap(year) returns True if the given year is a leap year, False otherwise.

  • calendar.leapdays(y1, y2) tells how many leap years are between year1 and year2 (exclusive of y2).

  • calendar.monthrange(year, month) returns a tuple (start_day, num_days) where start_day is the weekday index of the first day of that month and num_days is the number of days in the month.

These can be used for calculations or validations involving dates.

Using time and calendar together: Often you might get the current date/time with time and then use calendar for something. For instance, if you want to timestamp a backup file with the current date, you could do:

timestamp = time.strftime("%Y%m%d")  # e.g., "20250806" for Aug 6, 2025
backup_filename = f"backup_{timestamp}.zip"

Here we used time.strftime to get a compact date stamp. We could also have used datetime module for this, but this works fine for simple cases.

Another example: schedule something only on weekends:

today = time.localtime()
weekday_idx = today.tm_wday  # tm_wday: 0=Monday ... 6=Sunday
if weekday_idx >= 5:  # 5=Saturday, 6=Sunday
    print("It's the weekend, run maintenance tasks.")

(Note: tm_wday from time.localtime() uses Monday=0, Sunday=6 which aligns with calendar’s convention.)

The calendar module can produce outputs or compute values that might not be needed in every script, but it’s good to be aware of it. For our use, generating timestamps (with time) is likely more relevant, especially when naming backup files or logging times of operations.