An Overview of Python

1. What is Python?
2. Interpreted languages
3. Advantages and disadvantages
4. Downloading and installing
5. Which version of Python
6. Where to find documentation
7. Python Comments
8. Output to the screen
9. Running Python Scripts
10. Structure of a Python script
11. Using the interpreter interactively

1. Using variables
2. Assigning value to multiple variables
3. Expression
4. Math operators
5. String types: normal, raw and Unicode
6. String operators
7. Command line parameters
8. Reading from the keyboard

1. About flow control
2. Indenting is significant
3. The if statements
4. The nested if statements
5. The elif statements
6. The for loops
7. The while loops
8. Loop Controls - break and continue
9. The range() function
10. Arrays

1. Syntax of function definition
2. Formal parameters
3. Global versus local variables
4. Passing parameters and returning values
5. Passing list of parameters
6. Variable length arguments
7. Lambda functions
8. Passing function to another function
9. Returning function
10. Inner functions

Working with Files

1. Text file I/O overview
2. Opening a text file
3. Reading text files
4. Raw (binary) data
5. Writing to a text file
6. Opening Excel File
7. Reading from Excel File
8. Writing data into Excel File

Sequence

1. List overview
2. List methods
3. Tuple overview
4. Tuple methods
5. Dictionary overview
6. Dictionary methods
7. Set overview
8. Set methods
9. Fetching values
10. Fetching keys
11. Testing for existence of elements
12. Deleting elements
13. Set Operators

Python Classes

1. About o-o programming
2. Defining classes
3. Class methods and data
4. Constructors
5. Objects
6. Instance methods
7. Instance data
8. Destructors
9. Interfaces
10. Inheritances

Errors and Exception Handling

1. Dealing with syntax errors
2. Exceptions
3. Handling exceptions with try/except
4. Cleaning up with finally

Using Modules

1. What is a module?
2. The import statement
3. Function aliases
4. Packages
5. Installing Packages from PYPI
6. Standard Modules – sys
7. Standard Modules – math
8. Standard Modules – time

Regular Expressions

1. RE Objects and Pattern matching
2. Parsing data
3. Subexpressions
4. Complex substitutions
5. RE tips and tricks

Highlights of the Standard Library

1. Working with the operating system
2. Grabbing web pages
3. Sending email
4. Using glob for filename wildcards
5. math and random
6. Accessing dates and times with datetime
7. Working with compressed files

Accessing Databases

1. Selecting Data
2. Inserting and Updating Data
3. Deleting data
4. Generic database API based on MySQL
5. Using the Object Relational Mapper (SQLAlchemy)
6. Working with NoSQL databases

Data distribution

1. Center
2. Spread
3. Shape – Symmetry, Number of peaks, Skewness, Uniform
4. Unusual Features – Gaps, Outliers
5. Measures of central tendency - Mean, Median, Mode, Midrange
6. Measures of spread - Range, Variation, Standard deviation, Interquartile range
7. Measures of shape - Empirical rule, Chebyshev's rule, Skewness, Kurtosis
8. Measures of relative position – Quartiles, Percentiles, Midquartile

Extract data from Website - Beautiful soup

1. Installing Beautiful Soup
2. Installing a parser
3. Making the soup
4. Kinds of objects
5. Navigating the tree
6. Managing the tree
7. Searching the tree
8. Append the tree
9. Insert inside the tree
10. Extract, decompose, replace with,
11. wrap and unwrap
12. Pretty-printing
13. Non-pretty printing
14. Output formatters
15. Get Text
16. Output Encoding
17. Unicode

Selenium IDE

1. Selenium Overview
2. Selenium IDE Introduction
3. Downloading and Installing Selenium IDE
4. Recording and Running a Simple Test
5. Selenium IDE – Features
6. Installing Useful Tools for Writing Tests
7. Selenium Concepts

Selenium Webdriver

1. Introduction to selenium webdriver
2. Advantages of webdriver
3. Downloading and configuring Webdriver
4. Converting Selenium IDE test to programming language (Python)
5. Detailed discussion about webdriver commands
6. Handling different browsers
7. Create our own methods in Webdriver
8. Using RC commands from webdriver project

Python for Data Analysis – NumPy

1. Introduction
2. Ndarray Object
3. Data Types
4. Array Attributes
5. Array Creation Routines
6. Array from existing data
7. Numerical ranges
8. Array Indexing and Slicing
9. Advanced Indexing
10. Iterating over Array
11. Array Manipulation
12. Arithmetic Operators
13. Binary Operators
14. String Functions
15. Mathematical Functions
16. Statistical Functions

Python for Data Analysis – Pandas

1. Introduction to Pandas
2. Series
3. DataFrames
4. Missing Data
5. Group By
6. Merging Joining and Concatenating
7. Operations
8. Data Input and Output

Python for Data Visualization

1. Matplotlib
2. Seaborn
3. Distribution Plots
4. Categorical Plots
5. Matrix Plots
6. Grids
7. Regression Plots
8. Pandas Built-in Data Visualization
9. Plotly
10. Cufflinks
11. Geographical Plotting
12. Choropleth Maps

Python for Data Analysis – SciPy

1. Introduction
2. Basic functions
3. Special functions
4. Integration
5. Optimization
6. Interpolation
7. Fourier transforms
8. Signal Processing
9. Linear Algebra
10. Sparse Eigenvalue Problems with ARPACK
11. Compressed Sparse Graph Routines
12. Spatial data structures and algorithms
13. Statistics
14. Multidimensional image processing