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Data Science with Python

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Data Science with Python

The main objective of our course is to enable you to learn Data Science with Python programming language in a professional manner.

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  • ৳ 6,000
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Sk Hapijul Hossen
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What you will learn

  • Learn Python programming for data science from scratch.
  • To clean and prepare data for machine learning.
  • Understand the story your data is telling by summarizing the data and examining its variability and shape.
  • Understand and apply supervised and unsupervised learning algorithms.
  • Works in real-life use cases.

Course Content

15 sections • 55 lectures • 05h 09m total length
2.1 Statistics and Probab
16.40min
2.2 Statistics and Probab
15.16min
3.1 Python for Data Science
2.5min
3.2 Python for Data Science
5.57min
3.3 Python for Data Science
5.46min
3.4 Python for Data Science
6.48min
3.5 Python for Data Science
5.9min
3.6 Python for Data Science
3.46min
3.7 Python for Data Science
2.33min
3.8 Python for Data Science
4.39min
3.9 Python for Data Science
2.55min
3.10 Python for Data Science
5.26min
4.1 Installation_and_Configuration
5.43min
4.2 Setup
4.4min
4.3 SELECT_DISTINCT_WHERE
4.51min
4.4 WHERE_with_AND_OR_NOT
5.55min
4.5 SQL_LIKE
4.27min
4.6 Aggregate Functions_ LIMIT
6.04min
4.7 Alias_IN_BETWEEN
4.16min
5.1 Introduction to Web Scraping
2.08min
5.2- Interacting with Web
4.33min
5.3 Fetching from APIs
4.55min
5.4- Fetching Multipage Data
3.26min
5.5- Downloading Images
5.28min
5.6- Fetching Web Source
1.52min
5.7- Extracting Information using BeautifulSoup
12.08min
5.8- Extracting All Quotes
5.29min
5.9- Web Crawling on Multiple Pages
10.40min
7.1 Line Plot
11.27min
7.2-BarPLot
4.04min
7.3-Histogram
2.30min
7.4-Scatter
2.29min
7.5-PieChart
3.09min
7.6 DPlot
4.18min
7.7 Live PLot
3.54min
11.1.1 Logistic Regression
7.57min
11.1.2 Data Preparation for Model
14.23min
11.1.3 Evaluation of Classification
5.58min
11. 1.4 Testing
4.17min
11. 1.5 Evaluating Model
https://vimeo.com/712817020min
11.1.6 Cross Validation 1
2.45min
11.1. 7 Cross Validation-2
12.20min
11.1.8 Visualization of Data
3.55min
11.1. 9 Model Visualization
16.28min
11.2.1-KNN-Classification
2.16min
11.2.2-KNN-Data-Preparation
9.18min
11.2.3-KNN-Modelling
4.36min
11.2. 4-KNN-CrossValidation
2.29min
11.2. 6-KNN-Training with Best Parameters
2.16min
11.2.7-MOdel Visualization
5.32min
11.3.1 Decision Tree Classification
12.32min
11.3.2 Data Preparation
2.57min
11.3.3 Modeling _Evaluation
5.21min
11.3.4 Parameter Optimization
5.23min
11.3.5 Model Visualization
3.05min