Non-Certification Course

Data Collection and Processing with Python

The Data Collection and Processing with Python course focuses on extracting and handling data from Internet services through Python. Participants will learn about list comprehensions, nested data processing, utilizing the requests module to interact with REST APIs, and comprehending API documentation. The course offers hands-on practice in data extraction and processing, allowing learners to gain practical experience in these essential skills.

RM 2,600.00

per person

Level

Intermediate

Duration

2 Days

Training Delivery Format

Face-to-face / Virtual Class

RM 2,600.00

per person

Level

Intermediate

Duration

2 Days

Training Delivery Format

Face-to-face (F2F) / Virtual Class

Class types

Public Class

Private Class

In-House Training

Bespoke

This Data Collection and Processing with Python course teaches you to fetch and process data from services on the Internet. It covers Python list comprehensions and provides opportunities to practice extracting from and processing deeply nested data. You’ll also learn how to use the Python requests module to interact with REST APIs and what to look for in the documentation of those APIs.

The course is well-suited for you if you have already taken the “Python Basics” and “Python Functions, Files, and Dictionaries” courses. If you are already familiar with Python fundamentals but want practice at retrieving and processing complex nested data from Internet services, you can also benefit from this Data Collection and Processing course without taking the previous two.

The Data Collection and Processing is suitable for those who are just starting out in programming.

The Data Collection and Processing with Python course is well-suited for you if you have already taken the “Python Basics” and “Python Functions, Files, and Dictionaries” courses.

Module 1: Nested Data and Nested Iteration

In this module, you will cover more complex data structures. By the end of this week, you will have learned how to process json formatted data, traverse nested data using nested iteration, and extract values from nested data.

  • Nested Data
  • Nested Lists
  • Nested Dictionaries
  • JSON Format and the JSON Module
  • Processing JSON Results
  • Nested Iteration
  • Structuring Nested Data
  • Shallow Copies
  • Deep Copies
  • Extracting from Nested Data
  • A Worked Example of Nested Iteration

Module 2: Map, Filter, and List Comprehensions

In module two you will be learning more advanced forms of accumulation. By the end of the part, you will have learned how to use the map and filter functions in combination with functions to transform or filter out data and store the resulting data in a new object. You will have also learned how to accumulate data using a list comprehension.

  • Map
  • Filter
  • List Comprehensions
  • List Comprehensions Example
  • Zip
  • The Hangman Blanked Function

Module 3: Internet APIs

In module three you will learn how to request data from the internet using Application Programming Interfaces (APIs). By the end of the week, you will have learned how to access data from a few APIs, cache data that you have requested, and also learned how to read and work with other APIs that were not touched on in the module.

  • REST APIs
  • URLs, Domain Names, and IP Addresses
  • Routing
  • HTTP: Behind the Scenes
  • URL Query Parameters
  • REST API URLs
  • The requests Module
  • Using REST APIs
  • Generating URLs with requests.get
  • Reading API Documentation: Datamuse
  • Debugging Calls to requests.get
  • Caching Response Content
  • The requests_with_caching Module
  • Practice with REST APIs
  • iTunes API
  • flickr API

Module 4: Sequence Mutation and Accumulation Patterns

We will present deeper knowledge on using lists, strings, and python objects in general. We will also cover how to use the accumulation pattern with lists and with strings. The final assignment will test your knowledge and skills through application, much like previous assessments and assignments did, though with a more difficult set of tasks now that you have learned the basics.

  • Transforming Sequences
  • Mutability
  • List Element Deletion
  • Objects and References
  • Aliasing
  • Cloning
  • Methods on Lists
  • Append vs. Concatenate
  • Non-Mutating Methods on Strings
  • String Format Method
  • The Accumulator Pattern with Lists
  • The Accumulator Pattern with Strings
  • Accumulator Pattern Strategies
  • Don’t Mutate A List That You Are Iterating Through

 

This is a non-certification course.

If you are looking for a certification, Pyhton Institute offers the best options for you to choose from.

You can start with PCEP, Certified Entry Level Python Programmer.

Then you can pursue PCAP, Certified Associate in Python Programming, and then PCPP, Certified Professional in Python Programming 1.

 

Q: What will I learn in this Data Collection and Processing with Python?

A: In this course, you will learn essential programming concepts and techniques in Python. The topics covered include working with complex data structures like nested lists and dictionaries, processing

JSON formatted data, traversing nested data through nested iteration, and extracting information from nested data. Additionally, you will explore advanced accumulation techniques using map, filter, and list comprehensions, as well as understand internet APIs and how to request and work with data from different APIs.

The course will also cover sequence mutation, accumulation patterns, and efficient data manipulation strategies.

Q: How will this Data Collection and Processing with Python help me in my career?

A: This course will provide you with valuable Python skills that are highly sought after in various industries. Python is widely used in web development, data science, software engineering, and automation.

By mastering the topics covered in this course, you will be well-equipped to pursue roles such as Python Developer, Software Engineer, Data Scientist, and many more. Python’s versatility and popularity make it a valuable asset in today’s job market, allowing you to advance your career and contribute to innovative projects.

Q: What prerequisites do I need for this Data Collection and Processing with Python course?

A: This Data Collection and Processing with Python course is designed for learners with some prior programming experience, preferably in Python. Familiarity with basic programming concepts like variables, loops, and conditional statements will be beneficial. However, even if you are new to Python, the course offers explanations and examples to help you grasp the concepts effectively.

Q: How is the course structured, and what is the teaching approach?

A: The Data Collection and Processing course is divided into different modules, each focusing on specific topics and techniques. It starts with foundational concepts and gradually progresses to more advanced subjects. The teaching approach involves a mix of theoretical explanations, practical examples, and hands-on exercises.

You will have opportunities to apply what you learn through assignments and projects. Additionally, the course may provide access to external APIs and real-world datasets, enabling you to work on practical applications, which enhances your learning experience.

At this time, this course is available for private class and in-house training only. Please contact us for any inquiries. 

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