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PYTHON For DATA SCIENCE Course Details
 

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Batch Date: July 29th @8:30AM

Faculty: Mr. Vijay (17+ Yrs of Exp,..)

Duration : 45 Days

Venue :
DURGA SOFTWARE SOLUTIONS at Maitrivanam
Plot No : 202, IInd Floor ,
HUDA Maitrivanam,
Ameerpet, Hyderabad-500038.

Ph.No: +91 - 9246212143, 80 96 96 96 96

 Syllabus:

PYTHON For DATA SCIENCE

1. Python Basics

• What is Python
• Why Python?
• Applications of Python
• Features of Python
• Versions of Python
• Installation of Python
• Python Modes of Execution
• Interactive mode of Execution
• Batch mode of Execution
• Python Editors and IDEs
• Python Data Types
• Python Constants
• Python Variables
• Comments in python
• Output Print(), function
• Input() Function :Accepting input
• Type Conversion
• Type(), Id() Functions
• Comments in Python
• Escape Sequences in Python
• Strings in Python
• String indices and slicing
• Operators in python
• Flow-Control stmts and loops

2. Collections in Python

• Introduction
• Lists
• Tuples
• Sets
• Dictionaries
• Operations on collections
• Functions for collections
• Methods of collection
• Nested collections
• Differences b/w list tuple and set and Dictionary

3. Functions : Functional Programming

• Defining a function
• Calling a function
• Properties of Function
• Examples of Functions
• Categories of Functions
• Argument types
• -default arguments
• -non-default arguments
• -keyword arguments
• -non keyword arguments
• Variable Length Arguments
• Variables scope
• Call by value and Call by Reference
• Passing collections to function
• Local and Global variables
• Recursive Function
• Boolean Function
• Passing functions to function
• Anonymous or Lamda function
• Filter() and map() functions
• Reduce Function

4. Modules : Modular Programming

• What is a module?
• Different types of module
• Creating user defined module
• Setting path
• The import statement
• Normal Import
• From … Import
• Module Aliases
• Reloading a module
• Dir function
• Working with Standard modules

ii. Packages

• Introduction to packages
• Defining packages
• Importing from packages
• --init--.py file
• Defining sub packages
• Importing from sub packages

5. OOPs : Object Oriented Programming

• OOPS Features
• Encapsulation
• Abstraction
• Class
• Object
• Static and non static variables
• Defining methods
• Diff b/w functions & methods
• Constructors
• Parameterized Constructors
• Built –in attributes
• Object Reference count
• Destructor
• Garbage Collection
• Inheritance
• Types of Inheritances
• Object class
• Polymorphism
• Over riding
• Super() statement

6. PDBC : Python DataBase Connection

• Introduction
• Installing mysql database
• Creating database users,
• Installing Oracle Python modules
• Establishing connection with mysql
• Closing database connections
• Connection object
• Cursor object
• Executing SQL queries
• Retrieving data from Database.
• Using bind variables executing SQL queries
• Transaction Management
• Handling errors

7. Files : File Handling

• Introduction
• Types of Files in Python
• Opening a file
• Closing a file
• Writing data to files
• Tell( ) and seek( ) methods
• Reading a data from files
• Appending data to files
• With open stmt
• Various functions

8. Errors : Exception Handling

• Types of errors
• Compile-Time Errors
• Run-Time Errors
• What is Exception?
• Need of Exception handling
• Predefined Exceptions
• Try, Except, finally blocks
• Nested blocks
• Handling Multiple Exceptions
• User defined Exceptions
• Raise statement

9. Introduction to Datascience

• Machine Learning Introduction
• Datasets
• Supervised /Unsupervised Learning
• Statistical Analysis
• Data Analysis
• Uni-variate/multi-variate analysis
• Corelation Analysis
• Algorithm types
• Applications

10. Python Data Processing

• Python Data Operations
• Python Data cleansing
• Python Processing CSV Data
• Python Processing JSON Data
• Python Processing XLS Data
• Python Relational databases
• Python NoSQL Databases
• Python Date and Time
• Python Data Wrangling
• Python Data Aggregation
• Python Reading HTML Pages
• Python Processing Unstructured Data
• Python word tokenization

11 . Pandas : Python for Data Analysis

• Introduction to Pandas
• Creating Pandas Series
• Creating Data Frames
• Pandas Data Frames from dictionaries
• Pandas Data Frames from list
• Pandas Data Frames from series
• Pandas Data Frames from CSV, Excel
• Pandas Data Frames from JSON
• Pandas Data Frames from Databases
• Extracing rows using loc and iloc
• Pandas dealing with rows and columns
• Pandas indexing and slicing
• Pandas Data Functionality
• Pandas Timedelta
• Creating Data Frames from Timedelta
• Pandas Groupings and Aggregations
• Pandas Merging and concatenating
• Converting Data Frames from list
• Creating Functions
• Converting Different Formats
• Pandas and Matplotlib
• Pandas usecases
• Working Examples
• Pandas Exercises

12. Numpy : Python for Data Analysis

• Introduction to Numpy
• Numpy Arrays
• Numpy Array Indexing
• 2-D and 3Dimensional Arrays
• Numpy Mathematical operations
• Numpy Flattening and reshaping
• Numpy Horizontal and Vertical Stack
• Numpy linespace and arrange
• Numpy asarray and Random numbers
• Numpy iterations and Transpose
• Numpy Array Manipulation
• Numpy and matplotlib
• Numpy Linear Algebra
• Numpy String Functions
• Numpy operations and usecases
• Numpy Working Examples

13. Matplotlib : Python for Data Visualizations

1) Matplotlib – Axes Class

i. axes() function
ii. add_axes() function
iii. ax.legend() function
iv. ax.plot() function

2) Matplotlib-Multiple Plots

i. creating multiple subplots
ii. Adding title to subplots
iii. Main title for all subplots
iv. Create diff subplot sizes
v. Set spacing b/w subplots

3) Working with legend

i. Matplotlib.pyplot.legend()
ii. Matplotlib.axes.Axes.legend()
iii. Changing legend position
iv. Changing legend fontsize
v. Multiple columns in legend
vi. Sigle legend for all subplots
vii. Manually adding legend
viii. Placing legend ouside the plot
ix. Remove legend border

4) Line Chart

i. Line plot styles
ii. Plot multiple lines
iii. Change line opacity
iv. Increase the thickness of a line
v. How to fill b/w the lines

5) Bar plot

i. Horizontal bar chart
ii. Stacked bar plot
iii. Stacked percentage bar plot
iv. Back-to-back bar plots
v. Annotate bars in grouped barplot

6) Histogram

i. Creating Cummulative Histogram
ii. Plotting 2 histograms together
iii. Overlapping histogram
iv. Binsize in Histogram
v. Working examples

7) Scatter plots

i. Adding a legend to a scatter plot
ii. Connect scatterplot points with line
iii. Scatter plot with multiple colors
iv. Increasing the size of scatter plots
v. Working examples

8) Pie Chart

i. Pie chart labels
ii. Pie Chart Startangle
iii. Pie chart explode
iv. Pie chart Shadow
v. Pie Chart colors
vi. Pie Chart Legend
vii. Pie Chart Legend with title
viii. Pie Chart Working examples

9) 3D Plots

i. Three-dimensional Plotting
ii. 3D Scatter Plotting in Python
iii. 3D Surface plotting in Python
iv. 3D Wireframe plotting in Python
v. 3D Contour Plotting in Python
vi. Surface plots and Contour plots in Python
vii. How to change angle of 3D plot in Python?

10) Working with images

i. Working with Images
ii. Working with PNG Images
iii. Displaying Image in Grayscale
iv. Plot a Point or a Line on an Image
v. How to Draw Rectangle on Image
vi. How to Display an OpenCV image

14. Seaborn - Python for Data Visualization

1. Styling Plots

  • Seaborn | Style And Color
  • Seaborn – Color Palette

2. Multiple Plots

  • seaborn.FacetGrid() method
  • seaborn.PairGrid() method

3. Scatter Plot

  • Scatterplot using Seaborn in Python
  • Visualizing Relationship between variables with scatter plots
  • How To Make Scatter Plot with Regression Line using Seaborn
  • Scatter Plot with Marginal Histograms in Python with Seaborn

4. Line Plot

  • Data Visualization with Seaborn Line Plot
  • Creating A Time Series Plot With Seaborn And Pandas
  • How to Make a Time Series Plot with Rolling Average in Python?

5. Bar Plot

  • Barplot using seaborn in Python
  • Seaborn – Sort Bars in Barplot

6. Count Plot

  • Countplot using seaborn in Python

7. Box Plot

  • Boxplot using Seaborn in Python
  • Horizontal Boxplots with Seaborn in Python
  • Seaborn – Coloring Boxplots with Palettes
  • How to Show Mean on Boxplot using Seaborn in Python?
  • How To Manually Order Boxplot in Seaborn?
  • Grouped Boxplots in Python with Seaborn
  • Box plot visualization with Pandas and Seaborn

8. Violin Plot

  • Violinplot using Seaborn in Python
  • How to Make Horizontal Violin Plot with Seaborn in Python?
  • How to Make Grouped Violinplot with Seaborn in Python?

9. Strip Plot

  • Stripplot using Seaborn in Python

10. Swarm Plot

  • Python – seaborn.swarmplot() method
  • Swarmplot using Seaborn in Python

11. Factor Plot

  • Python – seaborn.factorplot() method
  • Plotting different types of plots using Factor plot in seaborn

12. Histogram

  • How to Make Histograms with Density Plots with Seaborn histplot?
  • How to Add Outline or Edge Color to Histogram in Seaborn?

13. Pairplot

  • Python – seaborn.pairplot() method
  • Data visualization with Pairplot Seaborn and Pandas

14. KDE Plot

  • Seaborn Kdeplot – A Comprehensive Guide
  • KDE Plot Visualization with Pandas and Seaborn

15. Heatmap

  • Seaborn Heatmap – A comprehensive guide
  • How to create a seaborn correlation heatmap in Python?
  • How to create a Triangle Correlation Heatmap in seaborn – Python?
  • ColorMaps in Seaborn HeatMaps
  • How to add a frame to a seaborn heatmap figure in Python?

15. Plotly – Python for Data Visualization

• Line Chart using Plotly
• Bar chart using Plotly
• Histogram using Plotly
• Scatter plot using Plotly
• Bubble chart using Plotly
• Pie plot using Plotly
• Box Plot using Plotly
• Gantt Chart in plotly
• Contour Plots using Plotly
• Create Heatmaps using graph_objects class in Plotly
• Sunburst Plot using Plotly
• Polar Charts using Plotly
• Ternary Plots in Plotly
• 3D Line Plots using Plotly
• 3D Surface Plots using Plotly
• 3D Bubble chart using Plotly
• 3D Mesh Plots using Plotly
• Sankey Diagram using Plotly
• Quiver Plots using Plotly
• Treemap using Plotly
• How to make Custom Buttons in Plotly?
• How to make Range Slider and Selector in Plotly?
• Animated Data Visualization using Plotly Express

16. Python MongoDB

• Python MongoDB Tutorial
• Installing MongoDB on Windows with Python
• MongoDB and Python
• Create a database in MongoDB using Python
• Python MongoDB – insert_one Query
• Python MongoDB – insert_many Query
• Python MongoDB – Find
• Python MongoDB – Query
• Python MongoDB – Sort
• MongoDB python | Delete Data and Drop Collection
• Python Mongodb – Delete_one()
• Python Mongodb – Delete_many()
• Python MongoDB – Update_one()
• Python MongoDB – Update_many Query
• Python MongoDB – Limit Query
• Python MongoDB – create_index Query
• Python MongoDB – drop_index Query

17. Python MySQL

• Connect MySQL database using MySQL-Connector Python
• Python MySQL – Create Database
• Python: MySQL Create Table
• Python MySQL – Insert into Table
• Python MySQL – Select Query
• Python MySQL – Where Clause
• Python MySQL – Order By Clause
• Python MySQL – Delete Query
• Python MySQL – Drop Table
• Python MySQL – Update Query
• Python MySQL – Limit Clause