Data Science Approach from Scratch: An Easy Explanation
Updated on
Course overview
- Provider
- Udemy
- Course type
- Paid course
- Level
- Beginner
- Lessons
- 15 lessons
- Certificate
- Available on completion
- Course author
- Nizamuddin Siddiqui
-
- Data Science explanation in layman language and it's need
- 8 Mistakes made by people who want to start their career in Data Science
- 3 Myths about Data Science
- Data Types and Variables
- Definition of Data Cleaning and the errors that results in the need of Data Cleaning
- Feature Engineering
- Data Thinking Development
- Use of many Algorithms
- Example to select the best model in case of a classification problem
- Types of Learning Methods
Description
Welcome to the ultimate course on Data Science Approach from Scratch!!!
This course is your Best Resource for learning the use of Data Science.
We will be understanding the use of:
1. Data Science from a layman's perspective
2. Regression Algorithms
3. Classification Algorithms
4. Clustering Algorithms
5. Boosting Algorithms
6. Dimensionality Reduction Algorithms
Specifically, we will cover:
Linear Regression
Stepwise Regression
Polynomial Regression
Logistic Regression
Naive Bayes
Decision Trees
Random Forest
Support Vector Machine
Gradient Boosting
Principal Component Analysis and Linear Discriminant Analysis
K-means Clustering and Hierarchical Clustering
and much more!
Feel free to message me on Udemy if you have any questions about the course!
Thanks for checking out the course page, and I hope to see you inside the course!
Nizamuddin
Course Instructor
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