Python for Data Science: From Basics to Advanced in 2025
Published 2/2025
Created by Cipher Schools
MP4 | Video: h264, 1280×720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Beginner | Genre: eLearning | Language: English | Duration: 39 Lectures ( 22h 22m ) | Size: 14.4 GB
Master Python programming for data analysis, visualization, and machine learning with real-world projects.
What you’ll learn
Understand the core concepts of data science and its applications.
Set up a professional environment with tools like Anaconda, Google Colab, and Git.
Master advanced Excel techniques, including formulas, PivotTables, and macros.
Learn Python fundamentals and leverage libraries like NumPy and Pandas for data manipulation.
Create static and interactive visualizations using Matplotlib, Seaborn, and Plotly.
Develop skills in Power BI for building dynamic dashboards and reports.
Preprocess, clean, and prepare data for machine learning applications.
Work on real-world projects like chatbot development and image classification.
Requirements
Basic knowledge of computers and mathematics.
Familiarity with programming concepts is helpful but not required.
A PC or laptop with internet connectivity to run the tools and code.
A willingness to learn and work on practical, hands-on projects.
Description
Data science is one of the most in-demand fields of the decade, and this course, Python for Data Science: From Basics to Advanced in 2025, offers an in-depth learning experience that caters to beginners and professionals alike. Covering a broad spectrum of topics, from data analysis to machine learning, this course equips you with the tools and skills needed to excel in the field of data science.We start with a solid introduction to data science, exploring its significance, workflow, and essential tools and skills required to thrive. You’ll set up your environment with tools like Anaconda, Google Colab, and Git for version control, ensuring you have a seamless start to your journey. Next, we dive into Advanced Excel, where you’ll master data cleaning, pivot tables, formulas, and even macros for automation.The course transitions into Python for Data Science, where you’ll learn to manipulate data using NumPy and Pandas. Data visualization is a core skill, and you’ll explore Matplotlib, Seaborn, and Plotly to create both static and interactive visualizations.You’ll also learn to use Power BI for data modeling and creating dynamic dashboards. A thorough Statistics Deep Dive builds your foundation in advanced statistical measures, hypothesis testing, and inferential analysis.From data preprocessing and feature engineering to machine learning, you’ll explore supervised, unsupervised, and neural network models. Finally, apply your skills with real-world projects like building a chatbot and an image classifier.This comprehensive course will help you confidently enter the field of data science!
Who this course is for
Aspiring data scientists or professionals looking to transition into the data science field.
Students and beginners eager to learn data science from scratch.
Individuals preparing for interviews or advancing in competitive programming.
Professionals seeking to upskill in data science, visualization, and machine learning.
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