A Python work for absolute beginners - this will take you to a serious early intermediate level.
Introductory Python: Functional language constructs; Python syntax; Lists, dictionaries, functions and function objects; Lambda functions; iterators, exceptions and file-handling
Database operations: as much database knowledge as you need to do information modification in Python
Auto-generating spreadsheets: Kill the drudgery of reporting tasks with xlsxwriter; automated reports that merge database operations with spreadsheet auto-generation
Text processing and NLP: Pythons powerful tools for text processing - nltk and others.
Net site scraping using Pretty Soup: Scrapers for the New York Times and Washington Post
Machine Learning : Use sk-learn to apply machine learning techniques like KMeans clustering
Hundreds of lines of code with hundreds of lines of comments
Drill #1: Download a zipper file from the National Stock Exchange of India; unzip and method to find the three most actively traded securities for the day
Drill #2: Store stock-exchange time-series information for three years in a database. On-demand, generate a document with a time-series for a given stock ticker
Drill #3: Scrape a news article URL and auto-summarize in to three sentences
Drill #4: Scrape newspapers and a weblog and apply several machine learning techniques - classification and clustering to these
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udemy coupon :https://www.udemy.com/from-0-to-1-python/?couponCode=SAL_PYTHON
Introductory Python: Functional language constructs; Python syntax; Lists, dictionaries, functions and function objects; Lambda functions; iterators, exceptions and file-handling
Database operations: as much database knowledge as you need to do information modification in Python
Auto-generating spreadsheets: Kill the drudgery of reporting tasks with xlsxwriter; automated reports that merge database operations with spreadsheet auto-generation
Text processing and NLP: Pythons powerful tools for text processing - nltk and others.
Net site scraping using Pretty Soup: Scrapers for the New York Times and Washington Post
Machine Learning : Use sk-learn to apply machine learning techniques like KMeans clustering
Hundreds of lines of code with hundreds of lines of comments
Drill #1: Download a zipper file from the National Stock Exchange of India; unzip and method to find the three most actively traded securities for the day
Drill #2: Store stock-exchange time-series information for three years in a database. On-demand, generate a document with a time-series for a given stock ticker
Drill #3: Scrape a news article URL and auto-summarize in to three sentences
Drill #4: Scrape newspapers and a weblog and apply several machine learning techniques - classification and clustering to these
- - -
Premium Python Courses with Massive Discount
udemy coupon :https://www.udemy.com/from-0-to-1-python/?couponCode=SAL_PYTHON