Python for Data Science IBM Full Course | Analyzing Data with Python | Python Data Analysis
Python for Data Science IBM Full Course | Analyzing Data with Python | Python Data Analysis
🚀 Python for Data Science – IBM Full Course | Analyzing Data with Python | Python Data Analysis | Free & Beginner-Friendly! 🧠💻
Ready to dive into the world of Data Science? Learn Python from scratch with this FREE full course by IBM – perfect for beginners, students, and aspiring data scientists!
🔍 What You’ll Learn:
✅ Python basics & Understand the Data
✅ Python Packages for Data Science
✅ NumPy & Pandas for data analysis
✅ Data Preprocesssing for Analysis
✅ Exploratory Data Analysis (EDA)
✅ Descriptive Statistics and Regressions
✅ Intro to Machine Learning with Scikit-learn
✅ Hands-on projects & coding demos
🎯 Why You Should Learn Python for Data Science: ✨ Most in-demand skill in tech
✨ Powerful for data analysis & AI
✨ Backed by industry leader IBM
✨ Free certificate of completion (via IBM platform)
🎓 Course Highlights:
📚 Full video course – no sign-up required
🧑🏫 Taught by IBM experts
💼 Boost your resume & career
🛠️ Practical, real-world examples
Start learning TODAY and level up your skills!
Don’t forget to LIKE 👍, SUBSCRIBE 🔔, and SHARE with your fellow learners!
⬇️⬇️⬇️ Download the training material from below link
https://drive.google.com/file/d/1MwquD243I...
⏲️⏲️⏲️ Time Stamps ⏲️⏲️⏲️
00:00:00 Course Introduction
00:01:44 Understanding the Data
00:04:19 Python Packages for Data Science
00:06:55 Importing and Exporting Data in Python
00:11:14 Getting Started Analyzing Data in Python
00:15:42 Accessing Databases with Python
00:19:50 Data Pre-processing in Python
00:22:09 Dealing with Missing Values in Python
00:28:15 Data Formatting
00:31:48 Data Normalization
00:35:32 Binning
00:37:30 Turn Categorical Variable into Quantitative Variable in Python
00:39:41 Exploratory Data Analysis
00:41:10 Descriptive Statistics
00:45:58 Group By in Python
00:49:27 Correlation
00:52:06 Correlation – Statistics
00:54:52 Model Development
00:56:45 Linear Regression and Multiple Linear Regression
01:03:27 Model Evaluation Using Visualization
01:08:20 Polynomial Regression and Pipelines
01:12:55 Measures for In-Sample Evaluation
01:17:50 Prediction and Decision Making
01:23:02 Model Evaluation
01:30:41 Overfitting, Underfitting and Model Selection
01:35:10 Ridge Regression
01:39:47 Grid Search
#PythonForDataScience #AnalyzingData #MachineLearning #DataScience #PythonBeginners #NumPy #Pandas #FullCourse
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