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Packt via Coursera

Intermediate Python – Libraries, Tools & Practical Projects

Overview

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This course is designed to elevate your Python skills by teaching you how to leverage powerful libraries, tools, and practical projects. You will work with key Python libraries such as Pandas for data analysis, NumPy for scientific computing, and Bokeh for data visualization. Additionally, you will gain hands-on experience with real-world projects, like web mapping and building an interactive English thesaurus. Whether you're interested in automating tasks or diving deep into data analytics, this course prepares you to handle complex challenges with Python.

Throughout the course, you'll begin by mastering data manipulation with CSV, JSON, and Excel files. The journey continues with a focus on numerical computing using NumPy and creating interactive web maps with Python. You’ll also explore image and video processing, gaining the ability to work with computer vision and control webcams. In the final modules, you’ll develop apps that combine data analysis and visualization, culminating in the creation of an interactive web app for real-time data visualization.

This course is ideal for intermediate Python learners who want to advance their knowledge by working on practical applications. You’ll gain in-depth expertise in Python libraries, and by the end, you will be equipped to handle various types of data analysis and programming challenges using Python.

By the end of the course, you will be able to load and analyze datasets, manipulate and visualize data using advanced libraries like Pandas, NumPy, and Bokeh, create interactive web apps for data visualization, and handle image and video processing with Python.

Syllabus 10

  1. Using Python with CSV, JSON, and Excel Files 2 hours

    In this module, we will explore how to work with structured data formats like CSV, Excel, and JSON using the powerful Pandas library. You'll learn how to clean, organize, and analyze data using Python, as well as leverage tools like Jupyter Notebooks for a hands-on coding experience. By the end, yo…

  2. Numerical and Scientific Computing with Python and NumPy 55 minutes

    In this module, we will dive into the NumPy library, Python’s go-to tool for numerical and scientific computing. You’ll learn to manipulate arrays, perform efficient data operations, and convert visual information like images into structured numerical formats. This is essential groundwork for data…

  3. App 1: Web Mapping with Python: Interactive Mapping of Population and Volcanoes 2 hours

    In this module, we will build an interactive web map that visualizes volcanoes and population data using Python and Folium. You’ll practice file handling, loops, string manipulation, and function creation to dynamically add layers and markers. Finally, you’ll enhance your map with stylization and u…

  4. App 2: Building an English Thesaurus 1.5 hours

    In this module, we will apply Python fundamentals to create an English thesaurus app that can process user input, suggest correct spellings, and return definitions from JSON datasets. You’ll build in intelligent logic for fuzzy matching and learn to optimize the user experience. This project blends…

  5. Fixing Programming Errors 1 hour

    In this module, we will explore how to identify, understand, and resolve programming errors that may occur during development. From syntax and runtime errors to more complex issues, you’ll gain strategies to troubleshoot effectively. You’ll also learn how to ask better programming questions and wri…

  6. Image and Video Processing with Python 1.5 hours

    In this module, we will introduce computer vision fundamentals using OpenCV in Python. You’ll learn to load and modify images, detect faces, and capture video using your webcam. These skills form the foundation for more advanced image analysis and machine learning applications.

  7. App 3: Controlling the Webcam and Detecting Objects 1.5 hours

    In this module, we will create a webcam-based motion detector app that tracks moving objects in real time. You'll build logic to log timestamps of detected motion and save the data into CSV files. This hands-on project strengthens your understanding of video input, object detection, and file handli…

  8. Interactive Data Visualization with Python and Bokeh 1.5 hours

    In this module, we will harness the power of Bokeh to build interactive data visualizations with Python. You'll learn to create time-series graphs, line charts, and motion plots using webcam data. This module equips you to turn raw data into meaningful and visually compelling insights.

  9. App 4 (Part 1): Data Analysis and Visualization with Pandas and Matplotlib 2.5 hours

    In this module, we will dive deep into data analysis and visualization using Pandas and Matplotlib. You'll work with time-series data to analyze trends by day, week, and month, and create meaningful plots. With real-world datasets, you’ll learn to uncover patterns and draw insights for informed dec…

  10. App 4 (Part 2): Data Analysis and Visualization - in-Browser Interactive Plots 3.5 hours

    In this module, we will extend your data visualization skills into the browser using JustPy and Highcharts. You’ll learn to create interactive charts and graphs that respond to user actions and display complex datasets in engaging ways. From line plots to pie charts, you’ll build a full-featured da…

Advantages and disadvantages

Advantages

  • Structured courses with graded quizzes, assignments and deadlines you can reset.
  • A shareable certificate from the university or company when you pay.
  • Financial aid is often approved for students in India (apply 15 days before you need it).
  • Covers niche tools that universities don't teach.
  • Self-paced: start any time.
  • A clear syllabus (10 parts) you can see before you start.
  • Hands-on: you build or practise, not just watch.

Disadvantages

  • Paid after a 7-day free trial (Coursera Plus or per course).
  • Some courses can be audited for free, but graded work and certificates need payment.
  • Many courses are produced quickly from slides and screen recordings; read the reviews first.

Some points apply to every course of this kind; see how we rank.

This course is paid. Here is how to take it for free

  • Free trials: You can start a 7-day free trial for many individual courses, Specializations, or a Coursera Plus subscription to test full course features. Cancel before the seventh day if you do not want to be charged.
  • Financial aid: If you cannot afford the fee for a certificate, you can apply for financial aid through the link on the course home page by filling out an application about your background and goals.

Taught by

  • Packt - Course Instructors

Packt is in Tier 5: mass-produced or unclear of our institution ranking (40/100). Thousands of courses turned out quickly; check reviews first.

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