Course Description
<p>Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from noisy, structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains. Data science is related to data mining, machine learning and big data.</p>
Curriculum
- Introduction to Programming
- Introduction to Python and How Python Works
- Introduction to Python Basic Course Structure
- How to install Python
- How to run Python Program using Command Line Window, IDLE, Notepad
- How to install Anaconda and run jupyter notebook for python
- Comments, Identifier, Reserved Words and Constant in Python
- Variable in Python
- Data Type in Python
- Declaring and Intializing Variables in Python
- Operators in Python
- Implicit and Explicit Type Conversion in Python
- Output Statement or Print Function in Python
- Getting input from user or Input Statement or input Function in Python
- Escape Sequence in Python
- If Statement in Python
- Nested if Statement in Python
- if Statement with Logical Operator in Python
- Indentation in Python
- if else Statement in Python
- Nested if else Statement in Python
- if elif and if elif else Statement in Python
- range Function in Python
- For Loop and Nested for Loop in Python
- Enumerate() in Python with EXAMPLES
- While Loop and Nested while Loop in Python
- Break, Continue and Pass Statement in Python
- String in Python
- More on Strings(Access string using loop, repetitation and concatenation in string, mutable and immutable)
- String Formatting in Python
- String Methods in Python
- List in Python
- List methods in python
- More on Lists (Use loops with list, slicing in list, concatenation, repeatition, aliasing, copying and cloning in list)
- Nested List in Python
- Tuple and tuple methods in Python
- More on Tuple(Use loops with tuple, slicing tuple, concatenation, repeatition, aliasing, copying tuple, getting user input as tuple, modifying and deleting tuple)
- Nested Tuple in Python
- Set Type in Python
- Set methods in Python
- Nested Set in Python - FrozenSet
- Dictionary in Python
- Dictionary methods in Python
- More on Dictionary (Loop in Dictionary, Getting Dictionary input from user)
- Nested Dictionary in Python
- Function and How Function Work in Python
- Arguments and its types in Python
- Local and Global Variable in Python
- global Keyword and function in Python
- Passing and returning List, Tuple, Set, Dictionary in Function
- Recursion in Python
- Anonymous Function or Lambda Expression in Python
- Function Decorator in Python
- Ternary if
- List, Tuple, Set and Dictionary Comprehension in Python
- Nested Comprehension in Python
- Generator Function Yield Statement and Next Function in Python
- Type and isinstance Function in Python
- Len,min,max and sorted Function
- Zip method
- Filter, map Function in Python
- Tips and Tricks in Python
- Getting Help in Python
- Class and Object in Python
- Constructor in Python
- Inheritance in Python
- Constructor in Inheritance
- Method Overloading, Overriding and Method with super in Python
- Special (Magic/Dunder) Methods
- Exception Handling and Builtin Exception in Python
- User Defined Exception in Python
- Difference between Error and Exception and Warning in Python
- Installing VSCode and coding in VSCode
- Debugging in VSCode
- Introduction to Virtual Environments
- Using conda and virtual environments with VSCode
- Module in Python, Math module in python
- Datetime Class in Python
- Random, sleep in Python
- Functools(Reduce and Memoization), getpass(getpass and getuser) and sys Module
- if __name__ == "__main__"
- What is File and File Handling in Python
- Reading Files in Python
- Write Create Files in Python
- What is git/ What is Version control system?
- What is Github?
- How To Insatll Git
- Basic Commands: add, commit, push
- Undoing/Reverting/Resetting code changes
- Branches (Create, Merge, Delete)
- What is HEAD?
- .gitignore file
- Diff and Merge using vscode
- What is Pull Request?
- Brief intro to working with git, github with help of vscode and github desktop
- Introduction to Libraries
- Introduction to Web Scrapping - Beautiful Soup
- Project 1 - Web scraping table from wikipedia
- PyQt Tutorial: Python GUI Designer
- Project 2 - Making a simple calculator
- Image Manipulation with Pillow
- Project 3 - Adding logo into Multiple images at once.
- Data on the Web
- eXtensible Markup Language(XML)
- XML Schema
- Parsing XML
- JSON Introduction
- Encoding JSON Python Objects
- Decoding JSON Python Objects
- Connecting to a server
- A simple server-client program
- What is Database?
- Connect to Database in Python
- Create a Table
- Insert Record into Table
- Query and Fetchall
- Use the Where Clause
- Course Introduction
- Classroom and Chat media Setup and Overview
- Jupyter Notebook and Other required Media installation.
- Introduction to Data Science
- Numpy Array Creation
- Numpy Indexing
- Numpy Array Operation
- Numpy Problem
- Numpy Quiz
- Numpy Practical Application
- Numpy Exercise
- Series
- DataFrames
- Index Objects
- Reindex
- Drop Entry
- Selecting Entries
- Data Alignment
- Rank and Sort
- Summary Statistics
- Missing Data
- Index Hierarchy
- Reading and Writing Text Files
- JSON with Python
- HTML with Python
- Microsoft Excel files with Python
- Merge
- Merge on Index
- Concatenate
- Combining Dataframes
- Reshaping
- Pivoting
- Duplicates in DataFrames
- Mapping
- Replace
- Rename Index
- Binning
- Outliers
- Permutation
- GroupBy on DataFrames
- GroupBy on Dict and Series
- Aggregation
- Splitting Applying and Combining
- Cross Tabulation
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Creating and Customizing Our First Plots
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Bar Charts and Analyzing Data from CSVs
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Pie Charts
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Stack Plots
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Filling Area on Line Plots
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Histograms
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Scatter Plots
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Plotting Time Series Data
-
Plotting Live Data in Real-Time
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SubPlots
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Installing Seaborn
-
Histograms
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Kernel Density Estimate Plots
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Combining Plot Styles
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Box and Violin Plots
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Regression Plots
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Heatmaps and Clustered Matrices
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Data Projects Preview
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Titanic Project
- What is Plotly?
- Installation
- Line Plots
- Bar Charts
- Scatter Plot
- Pie Charts
- Histograms
- Box Plots
- Violin Plot
- Density Heatmap
- 3D Scatter Plots
- 3D Line Plots
- Scatter Matrix
- Map Scatter Plots
- Choropleth Maps
- Polar Chart
- Ternary Plot
- Facets
- Animated Plots
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Introduction to Machine Learning with Scikit Learn
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Linear Regression
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Linear Regression - Multivariate
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Logistic Regression
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Gradient Descent
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Save Trained Model
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One Hot Encoding
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Train Test Split
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Logistic Regression
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Logistic Regression - MultiClass
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Decision Tree
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Support Vector Machines
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Random Forest
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K Fold Cross Validation
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K Means
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Naive Bayes
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GridSearch
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Regularization
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KNN Classification
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PCA
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Bias VS Variance
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Bagging
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Logarithm
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MAD and STD
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Normal Distribution and Z Score
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Mean, Median, Mode, Percentile and Quantile
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Descriptive VS Inferential Statistics
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Log Normal Distribution
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Sin, Cos, Tan
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Cosine Similarity
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Hypothesis Testing
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What is EDA?
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2D, 3D plots and Findings
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Probability Density Function and KDE
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Calculate Cummulative Distribution Function
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Use of Mean, Variance, Standard Deviation
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Use of Median, Percentile, Quantile, IQR, MAD
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Box plot and Whiskers median, quantile, IQR
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Violin plots and why we use it
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Summarizing plots in english
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Univariate, Bivariate and Multivariate Analysis
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Multivariate probability density, contour plot
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Exercise
- Optimizing Agricultural Production
- What's Next after Data Science Basic
