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Software Engineering & AlgorithmsUdemy2023-11 Edition100% Free Video Course

Advance Python | Python for Datascience

Advance Python Course | Easy to learn, Python for Datascience is designed for all levels of students. This course is designed for students who are eager to master Python and pursue a career as a data analyst or data scientist. This course comprehensively covers advanced Python concepts and provides students with a strong foundation in programming and data analysis with a focus on data analysis, data visualization, and machine learning. What you will learn: Python basics Part 1: Dive into the basics of Python Part II: Further exploration of Python basics Advanced Python concepts List Comprehension and Generators file management Exception Handling Object Oriented Programming (OOP) Decorators and Metaclasses NumPy (extensive library coverage): Arrays and array operations Array indexing and truncation Broadcasting and Vectorization Mathematical functions and linear algebra Array manipulation and rearrangement Pandas (extensive library coverage): Pandas data structure Data manipulation and manipulation Data cleaning and preprocessing Amalgamation, merger and reorganization Display data: Advanced Matplotlib techniques Seaborn for displaying statistical data Plotly for interactive displays Geospatial Data Analysis Machine learning with Scikit-learn (extensive library coverage): Linear Regression Logistic Regression Support Vector Machine (SVM), Decision Tree, Random Forest Unsupervised Learning Model Validation Techniques Hyperparameter tuning and model selection Case studies and projects: House rent forecast Prediction of heart disease Customer segmentation Who is this course suitable for? Students interested in exploring data analysis, cleaning, and preprocessing techniques using Python will find this course useful for understanding how to work with data. For students eager to expand their knowledge beyond basic programming, this course covers advanced Python concepts, object-oriented programming, and more. Students who want to learn advanced Python concepts and are interested in the field of data science. Students and professionals in the field of machine learning and artificial intelligence who are looking to strengthen their understanding of Python for implementation and data analysis. Data analysts and data scientists looking to use Python for advanced data manipulation, analysis, and visualization tasks. Advance Python course specifications Python for Datascience Publisher:  Udemy Instructor:  Selfcode Academy Training level: beginner to advanced Training duration: 9 hours and 44 minutes Number of courses: 24

24 Video Lessons
30.3 Hours On-Demand
Created by Selfcode Academy
Uploaded Sep 2026
English
beginner to advanced
Advance Python | Python for Datascience
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Course Features:
30.3 hours on-demand video
24 complete lectures
1 downloadable project zip file(s)
Streamable on mobile, tablet & desktop
Self-paced curriculum with progress tracking
Direct MP4 downloads & offline video access
Verified course archives hosted on cloud infrastructure.

What You'll Master in this Course

Python basics
Part 1: Dive into the basics of Python
Part II: Further exploration of Python basics
Advanced Python concepts
List Comprehension and Generators
file management
Exception Handling
Object Oriented Programming (OOP)
Decorators and Metaclasses
NumPy (extensive library coverage):
Arrays and array operations
Array indexing and truncation
Broadcasting and Vectorization
Mathematical functions and linear algebra
Array manipulation and rearrangement
Pandas (extensive library coverage):
Pandas data structure
Data manipulation and manipulation
Data cleaning and preprocessing
Amalgamation, merger and reorganization
Display data:
Advanced Matplotlib techniques
Seaborn for displaying statistical data
Plotly for interactive displays
Geospatial Data Analysis
Machine learning with Scikit-learn (extensive library coverage):
Linear Regression
Logistic Regression
Support Vector Machine (SVM), Decision Tree, Random Forest
Unsupervised Learning
Model Validation Techniques
Hyperparameter tuning and model selection
Case studies and projects:
House rent forecast
Prediction of heart disease
Customer segmentation

Course Curriculum24 Lectures

7 sections • 30.3 hours total length

Prefer offline learning? Download all 24 video lectures and project files for free.
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Requirements

  • Basic enthusiasm to learn and follow along with lessons
  • A computer or mobile device with a modern internet connection

Description

Advance Python Course | Easy to learn, Python for Datascience is designed for all levels of students. This course is designed for students who are eager to master Python and pursue a career as a data analyst or data scientist. This course comprehensively covers advanced Python concepts and provides students with a strong foundation in programming and data analysis with a focus on data analysis, data visualization, and machine learning. What you will learn: Python basics Part 1: Dive into the basics of Python Part II: Further exploration of Python basics Advanced Python concepts List Comprehension and Generators file management Exception Handling Object Oriented Programming (OOP) Decorators and Metaclasses NumPy (extensive library coverage): Arrays and array operations Array indexing and truncation Broadcasting and Vectorization Mathematical functions and linear algebra Array manipulation and rearrangement Pandas (extensive library coverage): Pandas data structure Data manipulation and manipulation Data cleaning and preprocessing Amalgamation, merger and reorganization Display data: Advanced Matplotlib techniques Seaborn for displaying statistical data Plotly for interactive displays Geospatial Data Analysis Machine learning with Scikit-learn (extensive library coverage): Linear Regression Logistic Regression Support Vector Machine (SVM), Decision Tree, Random Forest Unsupervised Learning Model Validation Techniques Hyperparameter tuning and model selection Case studies and projects: House rent forecast Prediction of heart disease Customer segmentation Who is this course suitable for? Students interested in exploring data analysis, cleaning, and preprocessing techniques using Python will find this course useful for understanding how to work with data. For students eager to expand their knowledge beyond basic programming, this course covers advanced Python concepts, object-oriented programming, and more. Students who want to learn advanced Python concepts and are interested in the field of data science. Students and professionals in the field of machine learning and artificial intelligence who are looking to strengthen their understanding of Python for implementation and data analysis. Data analysts and data scientists looking to use Python for advanced data manipulation, analysis, and visualization tasks. Advance Python course specifications Python for Datascience Publisher:  Udemy Instructor:  Selfcode Academy Training level: beginner to advanced Training duration: 9 hours and 44 minutes Number of courses: 24

Instructor

S

Selfcode Academy

Specialist in Software Engineering & Algorithms

Passionate educator focused on real-world practical skills, modern frameworks, and production-ready engineering practices. Delivering step-by-step masterclasses accessible to learners globally on MJ Accedemy.

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