Course details

Nitty-gritty of Data and Exploratory Analysis with Python 3

A brief summary

It’s been said that Data Scientist is the “most attractive job title of the 21st century.” According to

LinkedIn’s U.S. Emerging Jobs Report, the number of data science job has grown over 650%

since 2012. In our course, we will help you to become independent data analyst and make you

capable to start the journey for machine learning and AI domain. We will do it by hands on

practice and solving some real world problems.

Prerequisite

Computer Fundamental

Course highlight

  • Learn Advanced Python3.
  • Data scrapping (From web page / JSON based API).
  • Data mining and wrangling.
  • Exploratory Data analysis.
  • Introduction to Machine learning.

What you will learn

You will be able to learn all the important features of Python language

You will be able to write any code using Python language

You will have good understanding of Object Oriented Programming


01

Advanced python3 programming

Python data structures, List comprehension, Lambda, Map, Filter, Reduce functions and handling files.

02

Data scrapping

We will learn to scrape data from different websites using Urllib request and beautifulsoup. We will also learn to scrape data using JASON based API.

03

Data Analysis with Pandas/Numpy

We will learn all aspects of data analysis using pandas and numpy. We will cover topics such as Data input and validation, Series and Data Frames, indexing, Group by, stack-unstack, reshaping and Analysis.

04

Exploratory Data analysis

Here we will learn how to convert data into insights by converting them attractive visuals using matplotlib, pandas, seaborn etc. Here we will not only learn how to make charts and visuals; we will also learn the principles of information visualization. We will be introduced to tools for thinking about design and graphical heuristics for thinking about creating effective visualizations. We will learn how to discard noises and misleading information from charts also increase the truthfulness property of any visual.

05

Introduction to Machine Learning

In this section, we will introduce you to the world of machine learning and learn how to implement basic types of supervised learning algorithm (regression and classification) using pandas, numpy, scikit-learn and matplotlib.


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