| 0 | 204.8 B | ||
| 1. Course Introduction.mp4 | 13.9 MB | ||
| 1. Course Introduction.srt | 4.5 KB | ||
| 1. Creating and Calling Functions.mp4 | 23.7 MB | ||
| 1. Creating and Calling Functions.srt | 6.2 KB | ||
| 1. Date and time Data types.mp4 | 20.2 MB | ||
| 1. Date and time Data types.srt | 4.5 KB | ||
| 1. Decide Which Python Environment to Use.mp4 | 12 MB | ||
| 1. Decide Which Python Environment to Use.srt | 4.2 KB | ||
| 1. Handling Missing Data.srt | 3.4 KB | ||
| 1 | 0 B | ||
| 1. Handling Missing Data.mp4 | 13.2 MB | ||
| 1. Hierarchical Indexing.mp4 | 31.2 MB | ||
| 1. Hierarchical Indexing.srt | 6.5 KB | ||
| 1. Housing Dataset Analysis -Part One.mp4 | 10.8 MB | ||
| 1. Housing Dataset Analysis -Part One.srt | 4.2 KB | ||
| 1. Introducing Matplotlib Library.mp4 | 11.5 MB | ||
| 1. Introducing Matplotlib Library.srt | 3.2 KB | ||
| 1. Merging Datasets on Keys (common columns).mp4 | 36.9 MB | ||
| 1. Merging Datasets on Keys (common columns).srt | 8.2 KB | ||
| 1. Reading Data in Text Format-Part1.mp4 | 22.3 MB | ||
| 1. Reading Data in Text Format-Part1.srt | 5.8 KB | ||
| 1. Reshaping by Stacking and Unstacking.mp4 | 26.5 MB | ||
| 1. Reshaping by Stacking and Unstacking.srt | 5.6 KB | ||
| 1. Running Jupyter Notebook.mp4 | 28.8 MB | ||
| 1. Running Jupyter Notebook.srt | 5.9 KB | ||
| 1. Series in Pandas.mp4 | 24.6 MB | ||
| 1. Series in Pandas.srt | 5.9 KB | ||
| 1. Tuple.mp4 | 19.8 MB | ||
| 1. Tuple.srt | 5 KB | ||
| 1. What Is NumPy Arrays (Ndarrays).mp4 | 11.5 MB | ||
| 1. What Is NumPy Arrays (Ndarrays).srt | 2.9 KB | ||
| 10. Bar Plots with Dataframes.mp4 | 20.6 MB | ||
| 10. Bar Plots with Dataframes.srt | 4.2 KB | ||
| 10. Correlation and Covariance.mp4 | 18.7 MB | ||
| 10. Correlation and Covariance.srt | 4.1 KB | ||
| 10. Mathematical and Statistical Methods.mp4 | 35.4 MB | ||
| 10. Mathematical and Statistical Methods.srt | 6.6 KB | ||
| 10. String Object Methods.mp4 | 20.7 MB | ||
| 10. String Object Methods.srt | 4.8 KB | ||
| 11. Bar Plots with Seaborn.mp4 | 25.7 MB | ||
| 11. Bar Plots with Seaborn.srt | 5.6 KB | ||
| 11. Short Quiz.html | 204.8 B | ||
| 11. Sorting Arrays.mp4 | 21.2 MB | ||
| 11. Sorting Arrays.srt | 3.5 KB | ||
| 12. File Input and Output with Arrays.mp4 | 15.6 MB | ||
| 12. File Input and Output with Arrays.srt | 3.2 KB | ||
| 12. Histograms and Density Plots.mp4 | 27.8 MB | ||
| 12. Histograms and Density Plots.srt | 5.1 KB | ||
| 13. Scatter Plots and Pair Plots.mp4 | 35.8 MB | ||
| 13. Scatter Plots and Pair Plots.srt | 5.4 KB | ||
| 13. Short Quiz.html | 204.8 B | ||
| 14. Factor Plots for Categorical Data.mp4 | 27.3 MB | ||
| 14. Factor Plots for Categorical Data.srt | 6.4 KB | ||
| 15. Short Quiz.html | 204.8 B | ||
| 2. Converting Between String and Datetime.mp4 | 25.9 MB | ||
| 2. Converting Between String and Datetime.srt | 5.3 KB | ||
| 2. Creating Figures and Subplots.mp4 | 31.2 MB | ||
| 2. Creating Figures and Subplots.srt | 6.7 KB | ||
| 2. Creating Ndarrays.mp4 | 31.2 MB | ||
| 2. Creating Ndarrays.srt | 7.4 KB | ||
| 2. Dataframe in Pandas.mp4 | 34 MB | ||
| 2. Dataframe in Pandas.srt | 7.7 KB | ||
| 2. Filtering out Missing Data.mp4 | 20.3 MB | ||
| 2. Filtering out Missing Data.srt | 4.3 KB | ||
| 2. Housing Dataset Analysis -Part Two.mp4 | 23.3 MB | ||
| 2. Housing Dataset Analysis -Part Two.srt | 4.2 KB | ||
| 2. How to Download Course Notebooks.mp4 | 38.1 MB | ||
| 2. How to Download Course Notebooks.srt | 6.2 KB | ||
| 2. List.mp4 | 36.4 MB | ||
| 2. List.srt | 9.2 KB | ||
| 2. Local environment Installing Anaconda.mp4 | 10.4 MB | ||
| 2. Local environment Installing Anaconda.srt | 4.2 KB | ||
| 2. Merging Datasets on Index.mp4 | 15 MB | ||
| 2. Merging Datasets on Index.srt | 3.1 KB | ||
| 2. Reading Data in Text Format-Part2.mp4 | 21.6 MB | ||
| 2. Reading Data in Text Format-Part2.srt | 4.3 KB | ||
| 2. Reordering and Sorting Index Levels.mp4 | 14.3 MB | ||
| 2. Reordering and Sorting Index Levels.srt | 3 KB | ||
| 2. Reshaping by Melting (Wide to Long ).mp4 | 9.5 MB | ||
| 2. Reshaping by Melting (Wide to Long ).srt | 5.9 KB | ||
| 2. Returning Multiple Values.mp4 | 9.4 MB | ||
| 2. Tour In Basics of Jupyter Notebooks.mp4 | 26.9 MB | ||
| 2. Tour In Basics of Jupyter Notebooks.srt | 7 KB | ||
| 2 | 478.1 KB | ||
| 2. Returning Multiple Values.srt | 2.3 KB | ||
| 2.1 How to download course notebooks.pdf | 140.2 KB | ||
| 3. Basics of Time Series.mp4 | 32.8 MB | ||
| 3. Basics of Time Series.srt | 7.4 KB | ||
| 3. Cell Types in Jupyter Notebook.mp4 | 15.1 MB | ||
| 3. Cell Types in Jupyter Notebook.srt | 4.1 KB | ||
| 3. Changing Colors, Markers and Linestyle.mp4 | 21.9 MB | ||
| 3. Changing Colors, Markers and Linestyle.srt | 4 KB | ||
| 3. Cloud Environment Google Colab Jupyter Notebooks.mp4 | 20.2 MB | ||
| 3. Cloud Environment Google Colab Jupyter Notebooks.srt | 5.3 KB | ||
| 3. Concatenating Along an Axis.mp4 | 30.1 MB | ||
| 3 | 133.6 KB | ||
| 3. Concatenating Along an Axis.srt | 7.2 KB | ||
| 3. Data Types for Ndarrays.mp4 | 20.6 MB | ||
| 3. Data Types for Ndarrays.srt | 4.9 KB | ||
| 3. Dictionary.mp4 | 14.8 MB | ||
| 3. Dictionary.srt | 3.3 KB | ||
| 3. Filling in Missing Data.mp4 | 21.3 MB | ||
| 3. Filling in Missing Data.srt | 4.5 KB | ||
| 3. Housing Dataset Analysis -Part Three.mp4 | 29.7 MB | ||
| 3. Housing Dataset Analysis -Part Three.srt | 4.5 KB | ||
| 3. Index Objects.mp4 | 18.8 MB | ||
| 3. Index Objects.srt | 4 KB | ||
| 3. Lambda Functions.mp4 | 15.3 MB | ||
| 3. Lambda Functions.srt | 3.8 KB | ||
| 3. Overview of Course Curriculum.mp4 | 27.1 MB | ||
| 3. Overview of Course Curriculum.srt | 5.9 KB | ||
| 3. Reshaping by Pivoting (Long to Wide).mp4 | 28.9 MB | ||
| 3. Reshaping by Pivoting (Long to Wide).srt | 6.4 KB | ||
| 3. Summary Statistics by Level.mp4 | 17.3 MB | ||
| 3. Summary Statistics by Level.srt | 4.1 KB | ||
| 3. Writing Data in Text Format.mp4 | 21.9 MB | ||
| 3. Writing Data in Text Format.srt | 4.2 KB | ||
| 4. Arithmetic with NumPy Arrays.mp4 | 12.9 MB | ||
| 4. Arithmetic with NumPy Arrays.srt | 3.1 KB | ||
| 4. Customizing Ticks and Labels.mp4 | 28.6 MB | ||
| 4 | 225.7 KB | ||
| 4. Customizing Ticks and Labels.srt | 4.9 KB | ||
| 4. Generating Date Ranges.mp4 | 29.5 MB | ||
| 4. Generating Date Ranges.srt | 4.6 KB | ||
| 4. Getting Help in Jupyter Notebook.mp4 | 15.6 MB | ||
| 4. Getting Help in Jupyter Notebook.srt | 4.5 KB | ||
| 4. Housing Dataset Analysis -Part Four.mp4 | 31.9 MB | ||
| 4. Housing Dataset Analysis -Part Four.srt | 6.2 KB | ||
| 4. Indexing with Columns in Dataframe.mp4 | 23.1 MB | ||
| 4. Indexing with Columns in Dataframe.srt | 5 KB | ||
| 4. Reading Microsoft Excel Files.mp4 | 12.2 MB | ||
| 4. Reading Microsoft Excel Files.srt | 2.4 KB | ||
| 4. Reindexing in Series and DataFrames.mp4 | 13.4 MB | ||
| 4. Reindexing in Series and DataFrames.srt | 3 KB | ||
| 4. Removing Duplicate Entries.mp4 | 12.7 MB | ||
| 4. Removing Duplicate Entries.srt | 2.7 KB | ||
| 4. Set.mp4 | 4.5 MB | ||
| 4. Set.srt | 2.3 KB | ||
| 4. Short Quiz.html | 204.8 B | ||
| 5. Deleting Rows and Columns.mp4 | 5.4 MB | ||
| 5. Deleting Rows and Columns.srt | 3.2 KB | ||
| 5 | 113 KB | ||
| 5. Adding Legends.mp4 | 24.6 MB | ||
| 5. Adding Legends.srt | 4.4 KB | ||
| 5. Housing Dataset Analysis -Part Five.mp4 | 40 MB | ||
| 5. Housing Dataset Analysis -Part Five.srt | 8.7 KB | ||
| 5. Indexing and Slicing-Part One.mp4 | 17.8 MB | ||
| 5. Indexing and Slicing-Part One.srt | 4.2 KB | ||
| 5. Magic Commands.mp4 | 23.4 MB | ||
| 5. Magic Commands.srt | 4.2 KB | ||
| 5. Replacing Values.mp4 | 13.5 MB | ||
| 5. Replacing Values.srt | 3.5 KB | ||
| 5. Shifting Data Through Time (Lagging and Leading).mp4 | 33.2 MB | ||
| 5. Shifting Data Through Time (Lagging and Leading).srt | 6.6 KB | ||
| 5. Short Quiz.html | 204.8 B | ||
| 6. Adding Texts and Arrows on a Plot.mp4 | 23.4 MB | ||
| 6. Adding Texts and Arrows on a Plot.srt | 4.9 KB | ||
| 6. Handling Time Zone.mp4 | 33.5 MB | ||
| 6. Handling Time Zone.srt | 5.7 KB | ||
| 6. Indexing and Slicing-Part two.mp4 | 19.8 MB | ||
| 6. Indexing and Slicing-Part two.srt | 4.7 KB | ||
| 6. Indexing, Slicing and Filtering.mp4 | 25.3 MB | ||
| 6. Indexing, Slicing and Filtering.srt | 6.1 KB | ||
| 6. Renaming columns and Index Labels.mp4 | 11.2 MB | ||
| 6. Renaming columns and Index Labels.srt | 2.8 KB | ||
| 6 | 42.1 KB | ||
| 7. Adding Annotations and Drawings on a Plot.srt | 7.6 KB | ||
| 7. Arithmetic with Dataframe.mp4 | 22.1 MB | ||
| 7. Arithmetic with Dataframe.srt | 5 KB | ||
| 7. Boolean Indexing.mp4 | 28.2 MB | ||
| 7. Boolean Indexing.srt | 6.1 KB | ||
| 7 | 41.1 KB | ||
| 7. Adding Annotations and Drawings on a Plot.mp4 | 31.5 MB | ||
| 7. Filtering Outliers.mp4 | 22.4 MB | ||
| 7. Filtering Outliers.srt | 4.9 KB | ||
| 7. Resampling and Frequency Conversion.mp4 | 23.1 MB | ||
| 7. Resampling and Frequency Conversion.srt | 5.5 KB | ||
| 8. Fancy Indexing.mp4 | 18 MB | ||
| 8. Fancy Indexing.srt | 4.3 KB | ||
| 8. Rolling and Moving Windows.mp4 | 29.8 MB | ||
| 8. Rolling and Moving Windows.srt | 6.7 KB | ||
| 8. Saving Plots to a File.mp4 | 18.1 MB | ||
| 8. Saving Plots to a File.srt | 3.9 KB | ||
| 8. Shuffling and Random Sampling.mp4 | 20.9 MB | ||
| 8. Shuffling and Random Sampling.srt | 4.1 KB | ||
| 8. Sorting Series and Dataframe.mp4 | 20.3 MB | ||
| 8. Sorting Series and Dataframe.srt | 4.4 KB | ||
| 8 | 332.8 KB | ||
| 9. Descriptive Statistics with Dataframe.mp4 | 20.3 MB | ||
| 9. Descriptive Statistics with Dataframe.srt | 4.7 KB | ||
| 9 | 216.1 KB | ||
| 9. Dummy Variables.mp4 | 15.7 MB | ||
| 9. Dummy Variables.srt | 3.9 KB | ||
| 9. Line Plots with Dataframe.mp4 | 26.7 MB | ||
| 9. Line Plots with Dataframe.srt | 4.8 KB | ||
| 9. Short Quiz.html | 204.8 B | ||
| 9. Transposing Arrays.mp4 | 8.9 MB | ||
| 9. Transposing Arrays.srt | 2 KB | ||
| TutsNode.com.txt | 102.4 B | ||
| [TGx]Downloaded from torrentgalaxy.to .txt | 614.4 B | ||
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Description
This course is ideal for you, if you wish is to start your path to becoming a Data Scientist!
Data Scientist is one of the hottest jobs recently the United States and in Europe and it is a rewarding career with a high average salary.
The massive amount of data has revolutionized companies and those who have used these big data has an edge in competition. These companies need data scientist who are proficient at handling, managing, analyzing, and understanding trends in data.
This course is designed for both beginners with some programming experience or experienced developers looking to extend their knowledge in Data Science!
I have organized this course to be used as a video library for you so that you can use it in the future as a reference. Every lecture in this comprehensive course covers a single skill in data manipulation using Python libraries for data science.
In this comprehensive course, I will guide you to learn how to use the power of Python to manipulate, explore, and analyze data, and to create beautiful visualizations.
My course is equivalent to Data Science bootcamps that usually cost thousands of dollars. Here, I give you the opportunity to learn all that information at a fraction of the cost! With over 90 HD video lectures, including all examples presented in this course which are provided in detailed code notebooks for every lecture. This course is one of the most comprehensive course for using Python for data science on Udemy!
I will teach you how to use Python to manipulate and to explore raw datasets, how to use python libraries for data science such as Pandas, NumPy, Matplotlib, and Seaborn, how to use the most common data structures for data science in python, how to create amazing data visualizations, and most importantly how to prepare your datasets for advanced data analysis and machine learning models.
Here a few of the topics that you will be learning in this comprehensive course:
How to Set Your Python Environment
How to Work with Jupyter Notebooks
Learning Data Structures and Sequences for Data Science In Python
How to Create Functions in Python
Mastering NumPy Arrays
Mastering Pandas Dataframe and Series
Learning Data Cleaning and Preprocessing
Mastering Data Wrangling
Learning Hierarchical Indexing
Learning Combining and Merging Datasets
Learning Reshaping and Pivoting DataFrames
Mastering Data Visualizations with Matplotlib, Pandas and Seaborn
Manipulating Time Series
Practicing with Real World Data Analysis Example
Enroll in the course and start your path to becoming a data scientist today!
Who this course is for:
I designed this course to be valuable for people who are interested in data science and data analysis with python.
If you want to learn data science with python, this course will be a valuable starting point.
This course is for you if your intention is to learn how to use Python’s data science tools and libraries such as Jupyter notebook, NumPy, Pandas, Matplotlib, Seaborn, and related tools to effectively store, manipulate, and gain insight from data.
Requirements
It is advantageous to have basic python knowledge, but it is not required to understand the material in this course. However, people with no previous basic knowledge of python need to focus first on module 2, 3, 4, and 5, that would be enough to comprehend the rest material in this course.
Last Updated 9/2021
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
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Udemy - Complete Python Developer Bootcamp 2026 - Beginner to Advance Posted by
freecoursewb in Other
|
861.3 MB | freecoursewb | 1 month | 2 | 9 |
| 1 GB | freecoursewb | 2 months | 0 | 0 | |
| 2.9 GB | freecoursewb | 3 months | 16 | 2 | |
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Udemy - Python for Data Science - The Complete Data Science Bootcamp Posted by
freecoursewb in Other
|
3 GB | freecoursewb | 6 months | 18 | 3 |
| 28.7 GB | notimmune | 7 months | 34 | 9 |
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