This intensive, hands-on bootcamp is the entry point for professionals looking to automate tasks and understand the logic of programming. Designed for absolute beginners, this course strips away the complexity of software engineering and focuses on the practical scripts needed to move data, clean text, and automate file management. By the end of two days, you will be writing robust scripts that solve real workplace problems. All exercises are provided as guided notebooks with starter code. You will modify and extend working examples rather than starting from a blank page.

Learning Outcomes

By completing this bootcamp, you will be able to:

1. Write functional Python scripts (with guidance) to solve logic and automation problems.
2. Clean and format messy text data using string manipulation methods.
3. Control program flow using complex logic, loops, and conditional statements.
4. Organize data efficiently using Lists and Dictionaries.
5. Build reusable tools by writing custom Functions.
6. Read and write files (text and logs) automatically.
7. Handle errors gracefully using Try/Except blocks to prevent crashes.
8. Debug code confidently by understanding error messages.

Day 1: The Logic of Automation

Theme: From Zero to Scripting

Morning Session (9:00 AM - 12:30 PM)

9:00-10:30 | Welcome & Core Variables

• Topics:
  • Setup: Navigating Google Colab and code cells.
  • Data: Variables as "buckets" for storage (Integers, Floats, Strings).
  • Cleaning: String methods (.strip(), .upper(), .replace()) to fix messy inputs.
  • Formatting: Using F-strings for clean reports.
• Hands-On Activities:
  • Create your first notebook and fix a syntax error.
  • "The ID Cleaner": Write code to clean messy user IDs (e.g., " emp-123 ") into standard formats.
  • Build a "Mad Libs" generator to practice variable injection.
• You'll be able to: Navigate the environment and write scripts that clean and store text data.

10:30-11:00 | Morning Break

11:00-12:30 | The Logic Layer: Booleans & Conditionals

• Topics:
  • Making decisions with if, elif, else.
  • Comparison operators (>, <, ==, !=).
  • Logical operators (and, or, not).
  • Handling case sensitivity in logic.
• Hands-On Activities:
  • "Overtime Calculator": Write a script that applies different pay rates based on hours worked.
  • Build a simple login gatekeeper.
  • Create a tool that categorizes numerical values (High/Medium/Low).
• You'll be able to: Write programs that make "smart" decisions based on input data.

12:30-1:30 PM | Lunch Break

Afternoon Session (1:30 PM - 5:00 PM)

1:30-3:00 | Lists & Iteration (The Engine of Automation)

• Topics:
  • Creating Lists: Storing ordered data.
  • Indexing and Slicing: Extracting specific items.
  • For Loops: Iterating over data (doing the same task 1,000 times).
  • While Loops: Repeating until a condition is met.
  • Modifying lists: .append(), .remove().
• Hands-On Activities:
  • "The Email Validator": Loop through a list of emails and flag invalid ones.
  • Process a list of sales figures to find the total and average.
  • Build a dynamic "To-Do" list manager.
• You'll be able to: Write scripts that process large batches of data instantly.

3:00-3:30 | Afternoon Break

3:30-5:00 | Day 1 Mini-Project: "The Gatekeeper"

• The Challenge:
  • You will build a secure command-line login tool.
• Project Requirements:
  • Store a "correct" password in a variable.
  • Use a while loop to prompt the user for input (max 3 attempts).
  • Use string methods to handle accidental spaces in input.
  • Use if/else logic to grant access or lock the user out.
• You'll deliver: A working, interactive script that combines variables, loops, and logic.

Day 2: Structuring Code & Persistence

Theme: Building Robust Tools

Morning Session (9:00 AM - 12:30 PM)

9:00-10:30 | Dictionaries (The Key-Value Store)

• Topics:
  • Why Lists aren't enough: Labeled data.
  • Creating Dictionaries: Keys and Values.
  • Accessing nested data (e.g., User Profiles).
  • Looping through keys and values (.items()).
• Hands-On Activities:
  • "The Inventory Lookup": Build a tool that retrieves product prices by name.
  • Create a "Contact Book" that stores emails and phone numbers.
  • Write a loop that calculates the total value of a shopping cart dictionary.
• You'll be able to: Organize complex data structures effectively.

10:30-11:00 | Morning Break

11:00-12:30 | Functions (Reusable Automation)

• Topics:
  • The "DRY" Principle (Don't Repeat Yourself).
  • Defining functions with def.
  • Parameters vs. Arguments.
  • return values vs. print statements (Critical for data pipelines).
  • Scope: Local vs. Global variables.
• Hands-On Activities:
  • "The Tax Calculator": Write a reusable function to calculate tax for different employees.
  • Refactor your "ID Cleaner" from Day 1 into a reusable function.
  • Create a library of helper functions for common math tasks.
• You'll be able to: Write modular, professional code that can be reused across projects.

12:30-1:30 PM | Lunch Break

Afternoon Session (1:30 PM - 5:00 PM)

1:30-3:00 | File I/O & Error Handling

• Topics:
  • Reading text files: open(), .read(), .readlines().
  • Writing to files: Overwriting (w) vs. Appending (a).
  • Safety First: Using the with
  • Robustness: try and except blocks to handle missing files.
• Hands-On Activities:
  • "The Logger": A script that appends user actions to a txt file with timestamps.
  • Read a configuration file and load settings into a program.
  • Write a program that doesn't crash even if the file is missing.
• You'll be able to: Interact with the file system and write crash-proof code.

3:00-3:30 | Afternoon Break

3:30-5:00 | Capstone Project: "The Log Analyzer"

• The Challenge:
  • You will process a raw server log file containing hundreds of mixed messages (INFO, WARNING, ERROR) and generate a clean report.
• Project Steps:
  • Ingest: Write a function to safely open and read txt.
  • Parse: Loop through lines and use String methods to detect "ERROR" messages.
  • Count: Track statistics (e.g., "Total Errors Found: 15").
  • Report: Write the specific error lines to a new file called txt.
  • Protect: Wrap the logic in try/except to handle file paths.
• Required Deliverables:
  • A complete Colab notebook with commented code.
  • A generated text file report.

You'll deliver: A complete automation pipeline that reads, processes, and saves data.