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Advanced Python for Data Analysis: Build & Optimize

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Advanced Python for Data Analysis: Build & Optimize

Instructor: EDUCBA

Included with

Gain insight into a topic and learn the fundamentals.
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Implement client-server apps, chatbots, and database integration.

  • Optimize data analysis with NumPy arrays, matrices, and vectors.

  • Build scalable Python solutions using advanced techniques.

Details to know

Shareable certificate

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Assessments

20 assignments

Taught in English

Build your subject-matter expertise

This course is part of the Python for Data Science: Real Projects & Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate

There are 6 modules in this course

By the end of this course, learners will be able to apply advanced Python techniques, implement client-server networking, develop chatbot applications, integrate databases, and optimize data analysis with NumPy. Through hands-on lessons, you will analyze datasets, design efficient programs, construct socket-based applications, and execute SQL queries in Python.

This course is designed to bridge the gap between intermediate Python knowledge and professional data analysis applications. You will gain practical experience with PyCharm, explore real-time communication through networking, and master database integration for managing client data. The course also emphasizes high-performance computing with NumPy, from array creation to matrix operations and vectorized computations. What makes this course unique is its blended approach to Python, combining development environments, networking, chatbot building, database integration, and advanced data analysis into one complete package. By completing this course, learners will develop the technical skills and confidence to design scalable, real-world Python solutions for data-driven projects.

This module introduces learners to Python’s development environment, focusing on packages, modules, and the Anaconda distribution. Learners will also explore PyCharm IDE, mastering its installation, configuration, and usage for executing Python programs efficiently.

What's included

6 videos3 assignments

6 videos•Total 44 minutes
  • Introduction to Packages and Modules•4 minutes
  • Concept of Anaconda Distribution•4 minutes
  • Installation of PyCharm•10 minutes
  • Executing Programs in PyCharm•5 minutes
  • Methods of the List•11 minutes
  • Learning the Bolt Structure•10 minutes
3 assignments•Total 50 minutes
  • Graded - Python Development Environment Essentials•30 minutes
  • Working with Packages and IDEs•10 minutes
  • Advanced Python Fundamentals•10 minutes

This module covers the fundamentals of client-server architecture, focusing on message communication protocols and server addressing. Learners will also implement socket programming in Python to build reliable network applications.

What's included

7 videos3 assignments

7 videos•Total 51 minutes
  • Networking Aspect of Client Server•7 minutes
  • Message Communication of Client and Server•6 minutes
  • Server IP from Client to Server•6 minutes
  • Programming Aspect of Networking•7 minutes
  • Writing the Client and Server Code•11 minutes
  • Socket Programming for Server•5 minutes
  • Python Package for Multithreading•8 minutes
3 assignments•Total 50 minutes
  • Graded - Python for Networking and Communication•30 minutes
  • Foundations of Client-Server Networking•10 minutes
  • Implementing Socket Programming•10 minutes

This module introduces chatbot development and the basics of real-time communication. Learners will build client-side socket components and integrate them with chatbot servers to create functional chat applications.

What's included

6 videos3 assignments

6 videos•Total 36 minutes
  • Working with Chat Bot•8 minutes
  • Sending and Receiving Data•6 minutes
  • Working on Chat Bot Server•3 minutes
  • Creating and Importing Client Socket•10 minutes
  • Creating Message for Client•8 minutes
  • Learning to Create a Chat App•1 minute
3 assignments•Total 50 minutes
  • Graded - Building Chat Applications with Python•30 minutes
  • Chatbot Programming Basics•10 minutes
  • Client-Side Socket Development•10 minutes

This module focuses on integrating databases into Python applications. Learners will create and modify tables, execute queries, and update chat applications to manage client data effectively using SQLite.

What's included

10 videos4 assignments

10 videos•Total 86 minutes
  • PyCharm Databases and SQLite•8 minutes
  • Commands for Creating a Table•9 minutes
  • Inserting Values in Table•6 minutes
  • Connecting between Database and Python code•9 minutes
  • Query from Database•10 minutes
  • Making changes in Chat App•8 minutes
  • Decoding the Client info•5 minutes
  • Indexing the Client Element•11 minutes
  • Connection from Client at Address•9 minutes
  • Adding Email and Client Name•11 minutes
4 assignments•Total 60 minutes
  • Graded - Database Integration with Python•30 minutes
  • Using Databases in PyCharm•10 minutes
  • Querying and Modifying Data•10 minutes
  • Managing Client Data in Applications•10 minutes

This module emphasizes practical data analysis techniques in Python, including dataset handling, temperature conversions, and the use of comprehensions. Learners will also explore NumPy fundamentals for efficient numerical computations.

What's included

7 videos3 assignments

7 videos•Total 52 minutes
  • Analyzing the Data Sets•9 minutes
  • Coding for Converting Temperatures•5 minutes
  • Converting Temperature using List comprehension •10 minutes
  • Introduction to NumPy•8 minutes
  • Size of List•7 minutes
  • Memory Consumed By ND array•7 minutes
  • Python List and NumPy Arrays•6 minutes
3 assignments•Total 50 minutes
  • Graded - Data Handling and Analysis in Python•30 minutes
  • Practical Data Analysis with Python•10 minutes
  • Introduction to NumPy for Data Analysis•10 minutes

This module provides advanced knowledge of NumPy, including multidimensional arrays, slicing, reshaping, and mathematical operations. Learners will implement matrix manipulations and comparison operations for effective data analysis.

What's included

11 videos4 assignments

11 videos•Total 90 minutes
  • Creating NumPy Arrays•11 minutes
  • Different Dimensional Array in NumPy•11 minutes
  • Shape of an Array•8 minutes
  • Slicing•11 minutes
  • Slicing Continue•5 minutes
  • Arrays of Ones and Zeros•9 minutes
  • NumPy Example•7 minutes
  • NumPy Example Continue•6 minutes
  • Using Scalers with NumPy Arrays•8 minutes
  • Matrix Multiplication•8 minutes
  • Comparison Operations•6 minutes
4 assignments•Total 60 minutes
  • Graded - Advanced NumPy Operations•30 minutes
  • Creating and Reshaping Arrays•10 minutes
  • Practical Array Applications•10 minutes
  • Matrix and Comparison Operations•10 minutes

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Instructor

EDUCBA
1,640 Courses•336,724 learners

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