Advanced Python for Data Analysis: Build & Optimize

This course is part of Python for Data Science: Real Projects & Analytics Specialization

Instructor: EDUCBA

Access provided by Aimsun SLU

6 modules

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

6 modules

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.

Skills you'll gain

Tools you'll learn

Integrated Development Environments

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

20 assignments

Taught in English

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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.