Python - Bootcamp
This bootcamp is designed to provide a comprehensive foundation in Python with a focus on modular programming, scripting, and preparing students for Data Science and Machine Learning if they want to pursue it. We’ve also included a brief introduction to OOP for context, while maintaining a practical, hands-on approach throughout.
Session 1: Introduction to Python and Development Environment
• Welcome and Course Overview
o Introduction to Python and its role in scripting, automation, and data analysis.
o Setting expectations for the course.
• Setting Up the Development Environment
o Installing Python 3.x.
o Introduction to IDEs: Jupyter Notebooks, VS Code.
o Setting up and using virtual environments.
• Basic Python Syntax
o Writing your first Python script.
o Understanding indentation, comments, and basic code structure.
o Introduction to Python REPL and Jupyter Notebooks.
Session 2: Data Types, Variables, and Basic Operations
• Data Types
o Integers, floats, strings, booleans.
o Type conversion and casting.
• Variables and Assignment
o Naming conventions and dynamic typing.
• Basic Arithmetic and Logical Operations
o Arithmetic, comparison, and logical operators.
• Input/Output
o Accepting user input and formatting output
Session 3: Control Flow Statements
• Conditional Statements
o if, elif, else statements.
o Nesting conditions and using logical operators.
• Loops
o for and while loops.
o Loop control statements (break, continue, pass).
• Practical Exercises
o Building small programs that utilize loops and conditions (e.g., number guessing game).
Session 4: Functions and Modular Programming
•Defining Functions
o Function parameters, return values.
o Default and keyword arguments.
•Modular Programming
o Writing reusable functions.
o Organizing code into modules and using import.
•Practical Exercises
o Building a small modular program.
Section 5: Working with Lists, Tuples, and Dictionaries
• List
o Creating, accessing, and modifying lists.
o List methods (append(), remove(), etc.).
• Tuples
o Creating and using immutable sequences.
• Dictionaries
o Creating key-value pairs.
o Dictionary methods and practical use cases.
• Practical Exercises
o Building programs that utilize these data structures.
Section 6: File Handling and Exception Management
• File I/O
o Reading from and writing to text files.
o Using the with statement for file handling.
• Exception Handling
o Using try, except, else, finally blocks.
o Raising exceptions.
• Practical Exercises
o Implementing file I/O and handling exceptions in programs.
Section 7: Iterators, Generators, and Decorators
• Iterators
o Using built-in iterators.
o Creating custom iterators.
• Generators
o Creating generator functions with yield.
o Understanding the differences between generators and regular functions.
• Decorators
o Creating and using decorators.
• Practical Exercises
o Writing iterators, generators, and decorators for specific use cases (e.g., data streams).
Section 8: Working with External Libraries and APIs
• Introduction to Python Libraries
o Overview of useful libraries from the Python Standard Library (e.g., math, datetime).
o Installing and managing external libraries with pip.
• Using APIs
o Making HTTP requests with requests.
o Parsing and processing JSON data.
• Practical Exercises
o Building a small project that interacts with an external API (e.g., fetching and processing weather data).
Session 9: Data Handling (No Data Science Focus)
• Working with Data Formats
o Reading and writing CSV files with the csv module.
o Working with JSON files.
• Data Processing
o Simple data transformations and manipulation.
• Practical Exercises
o Writing scripts that process data from CSV and JSON files.
Session 10: Modular Project Development
• Project Structuring
o Best practices for structuring Python projects.
o Organizing code into multiple modules and separating concerns.
• Practical Exercises
o Begin working on a larger modular project (e.g., a text-based game, data processing script).
Session 11: Command-Line Tools and Scripting
• Command-Line Interfaces (CLI)
o Writing Python scripts that accept command-line arguments.
o Using argparse to create user-friendly CLIs.
• Automation and Scripting
o Automating tasks like file operations and data processing.
• Practical Exercises
o Building a command-line tool for automating a task (e.g., file renaming, batch data processing).
Session 12: Final Project and Presentation
• Final Project
o Completing and presenting the final project.
o Example Projects:
o Command-line tool for data processing.
o A text-based game.
o A Python script that interacts with an API.
• Project Presentation
o Presenting projects to peers.
o Discussing challenges, approaches, and solutions.
o Comprehensive Curriculum: AIN GenX offers a structured, hands-on approach to learning Python, covering everything from basic syntax to advanced concepts like data analysis, automation, and web development.
o Industry-Relevant Skills: The bootcamp emphasizes practical, in-demand skills, making it ideal for individuals seeking careers in data science, software development, or automation. Python's popularity in various industries draws participants looking to boost their employability.
o Experienced Instructors: AIN GenX likely employs skilled instructors who provide real-world insights, making learning engaging and applicable to industry needs.
o Project-Based Learning: Participants work on real-world projects throughout the bootcamp, giving them practical experience they can showcase in their portfolios. This is crucial for students transitioning into new career paths or those looking to build freelance profiles.
o Certification: Completing the Python Bootcamp at AIN GenX provides participants with a certification, validating their skills for potential employers or freelance clients.
o Networking and Community: Bootcamps at AIN GenX provide opportunities to network with peers, professionals, and industry experts, which can be beneficial for career development.
These factors contribute to the value and appeal of AIN GenX’s Python Bootcamp for individuals aiming to enhance their technical skills and career prospects.
o No Prior Programming Experience Required
This Python bootcamps are designed for beginners. You do not need any prior coding experience.
o Basic Computer Literacy
Participants should have a basic understanding of how to use a computer, including tasks such as installing software and working with files.
o Interest in Python Applications
Ideal candidates are those interested in fields where Python is widely used, such as data science, web development, automation, or software development.
o Commitment to Learning
Python bootcamps, like the one at AIN GenX, are often intensive. Candidates should be prepared to dedicate time to completing assignments, projects, and participating in class activities.
o Educational Background
While no formal degree is typically required, having a background in mathematics, engineering, or a related field may be helpful, especially if you're aiming to pursue data science or machine learning after the bootcamp.
o Hands-on Learning with Real Projects
The bootcamp emphasizes practical, project-based learning, allowing students to work on real-world Python projects. This gives participants the opportunity to apply what they learn immediately and build a portfolio to showcase their skills.
o Comprehensive Curriculum
The curriculum covers a wide range of topics from basic programming to advanced areas like data analysis, machine learning, automation, and web development. This broad coverage equips learners with versatile skills applicable in multiple industries.
o Experienced Instructors
AIN GenX’s bootcamp is led by industry experts who offer real-world insights and mentoring. This enhances the learning experience by providing relevant knowledge that aligns with current industry trends.
o Flexible Learning Mode
The bootcamp may offer flexible mode options, such as part-time or full-time tracks, which allows working professionals and students to learn at their own pace.
o Certification
Upon completing the bootcamp, participants receive a Python certification, which can help them stand out in the job market, demonstrating their proficiency and commitment to potential employers.
o Strong Focus on Freelancing Skills
AIN GenX provides Upwork training as part of the bootcamp, which is particularly valuable for those looking to work as freelancers. This adds a unique component by helping participants learn how to secure projects and work independently on platforms like Upwork.
o Cost-Effective Learning
Compared to longer university programs, bootcamps like AIN GenX’s offer fast-tracked, affordable training that can get you job-ready in a short period of time.
o Exposure to Modern Tools and Technologies
Participants get exposure to tools and libraries like Pandas, NumPy, Matplotlib, and more, ensuring they are equipped with the skills used by professionals in data analysis and machine learning.
o Data Science and Machine Learning
Python is the go-to language for data science and machine learning because of its powerful libraries such as Pandas, NumPy, Matplotlib, Scikit-learn, and TensorFlow. With these skills, you can work as a:
• Data Scientist
• Machine Learning Engineer
• Data Analyst
o Web Development
Python, with frameworks like Django and Flask, is widely used for building web applications. After learning Python, you can pursue careers in:
• Full-stack Web Development
• Backend Web Development
• API Development
o Automation and Scripting
Python's simplicity makes it ideal for automating repetitive tasks, which is highly valuable in areas such as system administration and software testing. You can use Python for:
• Task Automation
• DevOps and Cloud Engineering
• Test Automation Engineering
o Artificial Intelligence (AI) and Robotics
Python is also the core language for AI development, robotics, and deep learning. Learning Python through a bootcamp equips you with the fundamentals for roles like:
• AI Developer
• Robotics Engineer
• Deep Learning Specialist
o Financial Analysis and Fintech
In the finance industry, Python is used for analyzing large datasets, building financial models, and developing fintech applications. Potential roles include:
• Quantitative Analyst
• Financial Modeler
• Fintech Developer
o Game Development
Python is also used in game development, particularly with libraries like Pygame. While not the most popular in this domain, Python still has a place in smaller game projects and game logic development.
o Freelancing and Consulting
AIN GenX offer Upwork or freelancing guidance, enabling learners to work on short-term projects as Python developers, which could be an entry point for:
• Freelance Developer
• Independent Python Consultant
o Cybersecurity
Python is frequently used in cybersecurity for writing scripts, automating security protocols, and building ethical hacking tools, opening doors for positions like:
• Cybersecurity Analyst
• Ethical Hacker
• Penetration Tester
o Blockchain and Cryptocurrency
Python is increasingly popular in blockchain development for creating smart contracts and cryptocurrency algorithms, making it a critical skill for roles such as:
• Blockchain Developer
• Cryptocurrency Analyst
o Career Flexibility
Python's versatility allows professionals to switch industries easily, as it's used across various fields like healthcare, e-commerce, education, and logistics. Learning Python can help you pivot into tech-heavy roles within your existing industry.
What are the prerequisites for joining the Python bootcamp?
This Python bootcamps do not require any prior programming experience. Basic computer skills and a willingness to learn are usually sufficient. However, familiarity with basic mathematical concepts can be helpful, especially for data science tracks.
What will I learn in a Python bootcamp?
A Python bootcamp typically covers:
Basic Python syntax and programming fundamentals
Data structures and algorithms
Libraries like Pandas, NumPy for data analysis
Projects like building apps, data analysis, or machine learning
Is the bootcamp suitable for complete beginners?
Yes, this Python bootcamps are designed for complete beginners and start with the basics, making it accessible to people with little or no coding background.
What career opportunities can I pursue after completing the Python bootcamp?
Completing a Python bootcamp can open doors to various roles, including:
Data Analyst
Python Developer
Machine Learning Engineer
Web Developer
Automation Specialist
Freelancer in Python-related projects
What is the duration of the course?
The duration and format of the training is 4 weeks.
Is there a certification provided after completion?
Yes, most bootcamps, including those like AIN GenX, offer a certificate of completion. This certificate can be added to your resume and LinkedIn profile to showcase your skills to potential employers.
Instructor
Irfan Bakaly
Data Analyst
24+ years of experience in Data Analysis
Noor Surani
Data Analyst
Data Scientist
25+ years of experience in Data Analysis
Amynah Reimoo
Data Analyst
2+ years of experience in Data Analysis
Sohail Ahmed
Data Scientist
5+ years of experience
in Data Science
Haris Jafri
Data Scientist
2+ years of experience
in Data Science
Who this course is for:
Beginners to Programming, Aspiring Data Scientists/Analysts, Professionals Seeking Career Transitions, Students
Duration
● 2 Months (24 Hours)
Classes
● In-Person/Online
Schedule
- Day: Saturday's Only
- Timing: 2:30 to 05:30 pm (PST)
Starting From
● 18 January, 2025
Course Fee
● Online
Rs. 7,500/- (One Time Payment)
● In-Person:
Rs. 15,000/- (One Time Payment)
Account Details
Bank: Habib Bank Limited
Account Title: AIN GenX
Account No: 5910-70000512-03
IBAN No: PK08 HABB 0059 1070 0005 1203
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