Statistics for Data Science | Statistics & EDA Full Course - In 2 Hours | Tutorial for Beginners

In this 2-hour course, we cover the fundaments of Statistics and Exploratory Data Analysis for Machine Learning. It covers Hypothesis Generation, EDA & Statistics, Handling Missing Values, Evaluation Metrics, and Building First Predictive Model. Join us to learn the basics and get hands-on experience with real-world examples.

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Become a full-stack Data Scientist 🔥
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Sections 🔥
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0:00:00 Hypothesis Generation
0:09:03 EDA & Data Insights
0:15:44 Descriptive & Inferential Statistics
0:22:44 Missing Values
0:41:28 Categorical Variables
0:49:34 Outliers
0:58:14 Build First Predictive Model
1:23:23 Confusion Matrix
1:40:44 Precision & Recall
1:53:10 AUC-ROC Curve
1:58:02 Log Loss
2:03:59 Types of Error

🔥 Free Learning Resources

[Lakshvedhi]

very useful content. i am doing data science course but they don't teach this and not like this as well. thank you.

[preetshah]

Make a video on R Programming launguage

[priyeshsingh]

If possible please share the slide used in presentataion.