Ultimate Data Science Mastery: From Basics to Deep Learning
Focused View
9:25:46
1 -Data Science for Everyone Materials.zip
1 -Why Do We Need Data Literacy.mp4
07:57
2 -What is Data Science.mp4
08:29
3 -Data Science Workflow.mp4
05:38
4 -Data Type.mp4
07:05
5 -DIKW Pyramid.mp4
07:23
1 -Data-Driven Decision Making.mp4
11:26
2 -Business Analytics.mp4
07:37
3 -Machine Learning.mp4
11:32
1 -What is EDA.mp4
10:17
2 -Stevens Typology.mp4
05:52
3 -Univariate Analysis.mp4
22:28
4 -Multivariate Analysis.mp4
05:14
1 -Probability Basics.mp4
14:50
2 -Conditional Probability.mp4
11:48
3 -Bayes Theorem.mp4
15:30
1 -Data Cleaning.mp4
23:32
2 -Handling Missing Data.mp4
09:50
3 -Data Transformation.mp4
08:00
4 -Data Reduction.mp4
13:26
1 -Data Visualization for Univariate Analysis Part 1.mp4
09:44
2 -Data Visualization for Univariate Analysis Part 2.mp4
09:07
3 -Data Visualization for Univariate Analysis Part 3.mp4
07:30
4 -Data Visualization for Bivariate Analysis.mp4
08:39
5 -Data Visualization for Higher Dimensions.mp4
07:17
1 -Statistical Hypothesis Testing.mp4
07:20
2 -Probability Distribution.mp4
09:50
3 -Law of Large Numbers and Central Limit Theorem.mp4
06:31
4 -Hypothesis Testing Part 1.mp4
14:36
5 -Hypothesis Testing Part 2.mp4
07:40
1 -t-test.mp4
10:15
2 -Two-sample t-test.mp4
10:40
3 -Chi-Squared Test.mp4
10:55
1 -Correlation.mp4
14:28
2 -Regression.mp4
08:29
3 -Hypothesis Testing by Correlation and Hypothesis.mp4
09:01
4 -Multiple Regression Analysis.mp4
12:36
1 -Types of Machine Learning.mp4
07:52
2 -Regression.mp4
12:56
3 -Performance Metrics of Regression Models Part 1.mp4
08:18
4 -Performance Metrics of Regression Models Part 2.mp4
09:56
1 -What is Classification.mp4
04:53
2 -Logistic Regression.mp4
04:08
3 -Decision Tree.mp4
10:48
4 -Ensemble Learning.mp4
07:50
5 -Performance Metrics of Classification Models Part 1.mp4
06:33
6 -Performance Metrics of Classification Models Part 2.mp4
07:35
1 -What is Clustering.mp4
12:03
2 -Distance-Based Clustering.mp4
10:30
3 -K-Means Clustering.mp4
11:45
4 -Example Customer Segmentation.mp4
06:24
1 -What is Deep Learning.mp4
09:12
2 -Perceptron.mp4
07:59
3 -Multilayer Perceptron.mp4
08:22
4 -Artiricial Neural Network.mp4
10:41
1 -How to Train a Neural Network.mp4
09:33
2 -Optimization.mp4
11:55
3 -Regularization Part 1.mp4
08:24
4 -Reguralization Part 2.mp4
05:37
More details
Course Overview
This comprehensive data science course takes you from foundational concepts to advanced techniques like deep learning, covering everything from data preprocessing to predictive analytics in a practical, hands-on approach.
What You'll Learn
- Fundamentals of data science, machine learning and statistical inference
- Data visualization techniques for univariate and multivariate analysis
- Predictive modeling with regression, classification and clustering methods
Who This Is For
- Beginners who want to learn data science from scratch
- Managers implementing data-driven decision making
- Professionals seeking to upgrade their analytics skills
Key Benefits
- 14 comprehensive modules covering the complete data science workflow
- Practical skills for data-driven decision making
- Hands-on experience with machine learning and deep learning
Curriculum Highlights
- Data Science Fundamentals & DIKW Pyramid
- Exploratory Data Analysis & Visualization
- Predictive Analytics & Machine Learning
Focused display
Category
- language english
- Training sessions 58
- duration 9:25:46
- Release Date 2025/06/10
