Data analytics with Python & Advanced Python Module

Note: The Program requires basic knowledge of Python

Data Analytics with Python    

With the advent of big data over the last decade and storage becoming cheaper, organizations are collecting a lot more data than before, making it imperative to derive insights from data and unlock the business value hidden in the data. Python is one of the most popular programming languages for data analysis. This course is designed for students who are familiar with a high level programming language like C, C++ or Java and would like to use Python for data analysis. The course provides a fast introduction to Python and then delves into Python data analysis

libraries – numpy, pandas, matplotlib and scikit-learn – and shows how to apply these libraries to practical dataanalytics problems

Chapter 1 – Introduction to Python

                     ● Python interpreter

                     ● Variables/Data Type

                     ● Loops/Conditionals

                     ● Functions

                     ● Data Structures – Lists and Maps

Chapter 2- Advanced Python

           ● Decorators

            ● Object Oriented Programming

            ● Functional Programming

           ● HTTP Protocol/Requests

Chapter  3 – numpy/pandas

● ndarray

● Vectorization

● Linear Algebra – Matrix operations

● Random number generation and sampling

● Series, DataFrame

● Summary Statistics

Chapter  4: Pandas/matplotlib

              ● Loading data – csv, sql

              ● Cleansing and Shaping data

              ● Grouping, filtering and joining

              ● Matplotlib – Figures and Subplots

              ● Matplotlib – Colors, Markers, Legends, Ticks, Lables

              ● Matplotlib – Area, Pie, Bar, Line, Density, Scatter plots

Chapter  5: Scikit-learn

                ● Supervised vs Unsupervised Learning

                ● Model fitting – cost function

                ● Classification

                ● Linear and Logistic Regression

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