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Data Science with Python

Data Science with Python

Learn how to analyze, clean and filter data with Python Data Analysis libraries of Python.

(107 reviews)
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Description

Hi! Welcome to Data Science Course , the only course you need to become Data Analyst / Data Scientist.

Here are some more details of what you get with This Course:

  • Introduction to Python Language – Learn the basics of Python Language, variables, loops, logic, Strings, Lists, Sets, Dictionary, Tuple, Exception handling, I/O, Modules, Regular Expressions and more...
  • Data Analysis – Using powerful libraries like Numpy, Pandas, Matplotlib and Scipy analyze, clean and filter the data in various formats.
  • Live Project – Work on a Live Project with data sets from various websites like kaggle and host the solution on your own website.

Courses Curriculum

  • Section 1: Introduction to Python
    • 01. • Installation and Working with Python
    • 02. • Understanding Python variables
    • 03. • Python basic Operators.
    • 04. • Understanding python blocks
    • 05. • Declaring and using Numeric data types: int, float, complex
    • 06. • Using String data type and String operations
    • 07. Getting input from user
    • 08. Converting from one data type to other
  • Section 2: Data Structures & Logic building
    • 01. Lists, Sets and Tuples
    • 02. Dictionary
    • 03. Slicing and other List & dictionary manipulation functions
    • 04. • Programming using string, list and dictionary in build functions
  • Section 3: Python Program Flow Control
    • 01. • Conditional blocks using if, else and elif
    • 02. • Simple for loops in python
    • 03. • For loop using ranges, string, list and dictionaries
    • 04. • Use of while loops in python
    • 05. • Loop manipulation using pass, continue, break and else
    • 06. • Powerful Lamda function in python
    • 07. List and Dictionary Comprehensions
  • Section 4:Functions
    • 01. Defining Functions
    • 02. Positional, default,keyword,*args, **args
    • 03. Return Types of functions
    • 04. Passing functions to functions
    • 05. Generator functions
    • 06. Iterators
    • 07. Decorators
    • 08. Map, Reduce, Filter, FrozenSet, Defaultdict
  • Section 5: Exception Handling
    • 01. Errors
    • 02. Exception Handling with Try
    • 03. Handling multiple Exceptions
    • 04. Writing your own Exception
  • Section 6: File handling in Python
    • 01. Reading config files in python
    • 02. Writing log files in python
    • 03. Understanding read functions, read(), readline() and readlines()
    • 04. Understanding write functions, write() and writelines()
    • 05. Manipulating file pointer using seek
    • 06. Saving objects with Pickle
    • 07. Programming using file operations
  • Section 7: Python Object Oriented Programming – OOPS
    • 01. Concept of class, object and instances
    • 02. Constructor, class attributes and destructors
    • 03. Inheritance , overlapping and overloading operators
    • 04. Adding and retrieving dynamic attributes of classes
    • 05. Programming using Oops support
  • Section 8: Python Regular Expression
    • 01. Powerful pattern matching and searching
    • 02. Power of pattern searching using regex in python
    • 03. Password, email, url validation using regular expression
    • 04. Pattern finding programs using regular expression
  • Section 9: API calling with Python
    • 1. Using requests
    • 2. Download file contents with requests
    • 3. Using requests to post data
  • Section 10: Web Scraping with BeautifulSoup
    • 1. Navigating HTML structure with BS
    • 2. Navigating the HTML structure With Beautiful Soup
    • 3. Searching and Extract for specific tags With Beautiful Soup
    • 4. Creating new HTML elements With Beautiful Soup
    • 5. Modifying HTML with BeautifulSoup
  • Section 11: Numpy Library
    • 01. Creating Numpy Array - Why Numpy
    • 02. NumPy Array Manipulation
    • 03. Matrix in NumPy
    • 04. Operations on NumPy Array
    • 05. Reshaping NumPy Array
    • 06. Indexing NumPy Array
    • 07. Arithmetic operations on NumPyArray
    • 08. Sorting and Searching in NumPy Array
    • 09. NumPy and Random Data
    • 10. Universal Functions
  • Section 12: Pandas Tutorial
    • 01. Pandas Installation and Dataframe basics
    • 02. Different ways of creating Dataframes
    • 03. Read Write Excel CSV files
    • 04. Handling Missing data - fillna,dropna
    • 05. Handle missing data - replace function
    • 06. Group by
    • 07. Concating Dataframes
    • 08. Merge dataframes
    • 09. Pivot Tables
    • 10. Reshape dataframe using melt
    • 11. Stack Unstack
    • 12. Crosstab in Dataframes
    • 13. Read Write data from database
    • 14. Datetimeindex and resample
    • 15. Time series analysis
  • Section 13: Matplotlib
    • 01. Creating different types of plots
    • 02. Line Graph in matplotlib
    • 03. Stem plot in matplotlib
    • 04. Bar Charts
    • 05. Plotting Histograms
    • 06. Scatter Plots
    • 07. Stack Plots
    • 08. Box Plots
    • 09. Pie Charts
    • 10. Dynamic time series plots

What you'll learn

  • Basics of Python Language
  • Expertise in Logic Building
  • Writing classes and functions
  • Downloading data from APIs
  • I/O with Python
  • Data Analysis APIs
  • Data Visualization API
  • Web scraping API
  • Data Cleaning and filtering
  • Working with databases

Requirements

  • Zeal to Code.
  • Basic of Programming Languages.
  • Python, Pycharm/Anaconda, and other APIs

Who this course is for:

  • Beginners to programming languages
  • Students eager to learn about Data Analytics
  • Working on real time data and filtering data
  • Your first step towards a career in AI

Reviews

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Pawandeep Singh
Best Institute for Data Science

I am a student of btech IT currently doing six month training at 9i technology i am doing python with data science staff and all the faculty member are very friendly and supportive they helped me gain all the industrial exposure.

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Rahul Yadav
Exceptional!

I am a student of dav college, I am doing Python data science course from here, and the teaching here is very good. And teachers are very helpful.

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Sukhman Saran
Perfect Institute!

I am student of B.Tech. IT currently on industrial training at 9i Technologies. I am doing course of Python with Data Science. This institute is best for learning new skills. Staff and all the faculty members are very friendly and supportive. They helped me gain all the industrial exposure.

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  • Classes : Monday - Friday
  • Doubt Session : Saturday
  • Daily Class: 2 Hours
  • Practice Time: Min 3-4 hours
  • Assessment: Online
  • Project Work: Live App
  • Language: English/Hindi
  • Video Recording: Available
  • Certificate: ISO Certified

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