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Course overview
You will Learn the key concepts and principles of data analysis, and how it can be used to drive business decision-making. Explore the different types of data analysis, and the research questions that can be answered using these data analysis techniques. Learn the basic functions and formulas for sorting, aggregating, and managing data for analysis in Microsoft Excel.
What will i learn?
- The skills to apply data analysis to business needs, including finance, sales, marketing, operations, and HR management.
- An understanding of how data is captured, stored, and accessed, with a theoretical introduction to databases and SQL.
- Highly practical Microsoft Excel skills that you can apply within your own context to analyse, interpret, and present data.
Curriculum for this course
47 Lessons
06:55:17 Hours
1. Introduction to this course
1 Lessons
00:03:06 Hours
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1.1. Intro to this course
00:03:06
2. Project 1-- Predict Fare of Airlines Tickets using Machine Learning
26 Lessons
04:38:11 Hours
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2.1. Introduction to Business Problem & Dataset
00:01:24
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2.2. Datasets & Resources.html
.
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2.3. Understanding Data & data-preprocessing
00:11:06
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2.4. Extract Derived Features from Data
00:10:59
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2.5. Perform Data Pre-processing
00:08:04
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2.6. Handle Categorical Data & Feature Encoding
00:12:09
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2.7. Perform Label Encoding on data
00:14:26
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2.8. How to handle Outliers in Data
00:07:53
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2.9. Select best Features using Feature Selection Technique
00:04:57
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2.10. Intuition Behind Random Forest Part-1
00:20:39
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2.12. Applying Random Forest on Data & Automate predictions
00:10:40
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2.13. Intuition Behind Decision Tree- Part 1
00:10:02
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2.14. Intuition Behind Decision Tree- Part 2
00:17:29
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2.15. Intuition Behind Decision Tree- Part 3
00:14:58
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2.16. Intuition Behind Decision Tree- Part 4
00:17:56
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2.17. Intuition Behind Decision Tree- Part 5
00:15:27
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2.18. Intuition Behind Decision Tree- Part 6
00:10:41
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2.19. Intuition Behind Linear Regression- Part 1
00:11:33
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2.20. Intuition Behind Linear Regression- Part 2
00:09:50
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2.22. Intuition Behind KNN- Part 1
00:12:34
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2.23. Intuition Behind KNN- Part 2
00:08:18
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2.24. Intuition Behind KNN- Part 3
00:07:28
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2.25. Intuition Behind KNN- Part 4
00:07:56
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2.26. Play with multiple Algorithms & dumping your model
00:07:56
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2.27. Intuition Behind Cross Validation- Part 1
00:10:45
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2.28. Intuition Behind Cross Validation- Part 2
00:13:01
3. Project 2----- Predict Password Strength using Natural Language Processing
10 Lessons
01:14:38 Hours
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3.1. Introduction to Business Problem & Dataset
00:01:14
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3.2. Datasets & Resources
.
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3.3. Exploring your data
00:08:25
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3.4. Intuition behind TF-IDF --part 1
00:08:30
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3.5. Intuition behind TF-IDF --part 2
00:08:15
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3.6. Apply TF-IDF on data
00:08:42
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3.7. Intuition behind Logistic Regression --part 1
00:13:52
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3.8. Intuition behind Logistic Regression --part 2
00:14:42
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3.9. Apply Logistic Regression on Data
00:07:06
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3.10. Checking Accuracy of Model
00:03:52
4. Project 3-- Predict Stock Prices using Time Series Analysis
10 Lessons
00:59:22 Hours
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4.1. Introduction to Business Problem & Dataset
00:01:30
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4.2. Datasets & Resources.html
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4.3. Analyzing Time Series data
00:05:17
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4.4. Data preparation for Time Series Forecasting
00:08:14
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4.5. Intuition behind ARIMA --part 1
00:04:41
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4.6. Intuition behind MA model --ARIMA part 2
00:12:13
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4.7. Intuition behind AR model -- ARIMA part 3
00:06:43
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4.8. Intuition behind Integrating -- ARIMA part 4
00:08:57
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4.9. Apply Auto-Arima on data
00:08:15
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4.10. Evaluating Time Series Model
00:03:32
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Updated Tue, 13-Jun-2023
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