Python Telugu Class-52 | Matplotlib Data Visualization-2 | Bhaskar Jogi | Go Online Trainings

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PYTHON COURSE CONTENT
Module 1: Python Core
1. Introduction of python and comparison with other programming languages
2. Installation of Anaconda Distribution and other python IDE
3. Python Objects, Numbers & Booleans, strings, Container objects, Mutability of objects
4. Conditions (if else , if -elif-else)
5. Loops (while, for)
6. Break and Continue Statements
7. Operators - Arithmetic, Bitwise, comparison and Assignment
8. Operators, Operators Precedence and associativity.
9. Range functions
Module 2: String Objects and collections
1. String object basics
2. String methods
3. Splitting and Joining Strings
4. String format functions
5. List object basics
6. List methods
7. List as stack and Queues
8. List comprehensions
Module 3: Tuples, Set, Dictionaries & Functions
1. Tuples, Sets, Dictionary Object basics, Dictionary
2. Object methods, Dictionary View Objects.
3. Functions basics, Parameter passing, Iterators
4. Generator functions
5. Lambda functions
6. Map, Reduce, filter functions
Module 4: OOPS concepts & Working with Files
1. OOPS basic concepts
2. Creating classes and Objects
3. Inheritance, Multiple Inheritances
4. Working with files
5. Reading and writing files
6. Buffered read and write
7. Other File methods
Module 5: Modules, Exception Handling & Database Programming
1. Using Standard Module
2. Creating new modules
3. Exceptions Handling with Try-except
4. Creating, inserting and retrieving Table
5. Updating and deleting the data.
6. FILE
Module 6: Flash and Api’s
1. Flask introduction
2. Flask Application
3. Open linkFlask
4. App RoutingFlask
5. URLBuildingFlask
6. HTTP MethodsFlask
7. TemplatesFlask
Module 7: Visualisation
1. Matplotlib
2. Seaborn
3. Plotly
4. Cufflinks
Module 8: Python Pandas
1. Python Pandas - Series
2. Python Pandas -Data Frame
3. Python Pandas - Panel
4. Python Pandas - Basic Functionality
5. Function Application
6. Python Pandas -Re-indexing
7. Python Pandas - Iteration
8. Python Pandas - Sorting
9. Working with Text Data
10. Options & Customization
11. Indexing & Selecting Data
12. Statistical Functions
13. Python Pandas - Window Functions
14. Python Pandas - Date Functionality
15. Python Pandas -Time delta
16. Python Pandas - Categorical Data
17. Python Pandas - Visualization
18. Python Pandas - IOTools
Module 9 : Python Numpy
1. NumPy - Ndarray Object
2. NumPy - Data Types
3. NumPy - Array Attributes
4. NumPy - Array Creation Routines
5. NumPy - Array from Existing Data
6. Array from Numerical Ranges
7. NumPy - Indexing & Slicing
8. NumPy - Advanced Indexing
9. NumPy - Broadcasting
10. NumPy - Iterating Over Array
11. NumPy - Array Manipulation
12. NumPy - Binary Operators
13. NumPy - String Functions
14. NumPy - Mathematical Functions
15. NumPy - Arithmetic Operations
16. NumPy - Statistical Functions
17. Sort, Search & Counting Functions
18. NumPy - Byte Swapping
19. NumPy - Copies &Views
20. NumPy - Matrix Library
21. NumPy- Linear Algebra
Module 10: Exploratory Data Analysis
1. Feature Engineering and Selection
2. Building Tuning and Deploying Models
3. Analyzing Bike Sharing Trends
4. Analyzing Movie Reviews Sentiment
5. Customer Segmentation and Effective Cross Selling
6. Analyzing Wine Types and Quality
7. Analyzing Music Trends and Recommendations
8. Forecasting Stock and Commodity Prices
Module 11: Project Explanation
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