Course Name: Data Science With Python Power Bootcamp
Duration : 5 Days
Course Summary: The purpose of this course is to teach student how to make data analysis with Python. The course covers Python programming,
Rest API, Data Gathering, Data Preprocessing, Data Visualization and Data Analysis With Python Programming Language. Student will work with
the following data formats: txt, json, xlsx, csv, html, text, db(sql), png, jpg.
Course Index:
Part 1: PROGRAMMING LANGUAGE: PYTHON
Module 1: Language Overview
> Why Python is popular on many areas?
> Big Data and Database Management
> Data Science and Analysis
> Machine Learning (ML:
> Artificial Intelligence (AI:
> Network Programming and System Automation
Module 2: Standard Data Types
> The Python Standard Library
> Built-in Functions and Modules
> Basic Operators and Type Casting
> Numeric Data Types and Functions
> String Data Type and Functions
Module 3: Flow Control,
> if-else
> For loop
> While loop
> break and continue statements
Module 4: Functions
> Function Definition
> Scope Rules
> Recursion
> Random Module Functions
Module 5: Lists and Tuples
> Immutable vs Mutable Types
> List and Tuple Functions
> Comparison
> Conversion
> Multi-dimensional Lists and Tuples
Module 6: Dictionaries
> Key and Value Pairs
> Dictionary Functions
> Sorting and Converting
Module 7: External Libraries
> Important Libraries
> How to Install and Import
> Examples
Module 8:Basic File Operations
> Open a File with r/w/a/b Modes
> File Operations
> File and Directory Methods
Module 9:Exception Handling
> Exception Types
> Multiple Exceptions
> try and except block
> Finally expression
Part 2: REST API With Python
Module 1: List Comprehension
Module 2: What is Model Driven Automation
Module 3: What is HTTP ?
Module 4: How HTTP works ?
Module 5: What is Rest API
Module 6: What are API Data Formats?
Module 7: List Comprehension
Module 8: Parsing Public Colorado Population API With Python
Module 9: Parsing News API With Python
Module 10: Parsing NASA API With Python
Module 11: Parsing Capital Cities JSON With Python
Module 12: Parsing Star War JSON With Python
Part 3: DATA SCIENCE WITH PYTHON
Module 1: What is Data Science ?
Module 2: What is Artificial Intelligence ?
Module 3: The Relation Between Artificial Intelligence, Data Science, Machine Learning and Deep Learnig
Module 4: What Data Scientist Do ?
Module 5: Creating Data Frames From API, HTML, Python Data Types, Excel, Clipboard, JSON With Pandas
Module 6: Managing, Renaming & Replacing Data Frames With Pandas.
Module 7: Create & Manage Excel With Openpyxl With Pandas
Module 8: Making Multiple Querries-Locate With Pandas
Module 9: Pandas DataFrame: Append, Concat, Transpose, Merge, Cut
Module 10: Pandas Nunique & Value Counts
Module 11: HTML Parsing With Pandas, Requests Beautiful Soup
Module 12: Lambda
Module 13: Numpy
Module 14: Mean, Variance, Sigma, Median, Mod
Module 15: Matplotlib 1 Data Visualization
Module 16: Matplotlib 2 Subplots
Module 17: Matplotlib 3 Subplots Pie
Module 18: Matplotlib 5 With Pandas Data Reader
Module 19: Matplotlib 7 Customize Time Series (rotation, indent, time format)
Module 20: Matplotlib & Probability
Module 21: Matplotlib Annotate & Arrowprops
Module 22: Advanced 3D Visualization With Matplotlib
Module 23: Data Visualization With PyGoogleChart
Module 24: Data Visualization With Plotly
Module 25: Seaborn Lineplot, Scatterplot, Heatmap, Pairplot, Barplot, Catplot
Module 26: Heart Attack Data Analysis Project
Module 27: Parsing Big Data With ijson
Module 28: File & Index Management With Python
Module 29: Parsing Star Wars Episode 3 Scenario
Module 30: Regular Expressions Parsing Words.txt file
Module 31: Regular Expressions Kill Bill Phrase With regex101
Module 32: Regular Expressions Parsing Emails
Module 33: SQlite3 Introduction To SQlite3 Database Company
Module 34: SQLite3 Harvard Movies Project