Data science Training in kukatpally

Data science Training in Kukatpally

About this Course. The Introduction to Data Science class will survey the foundational topics in data science.  It Manipulation. Data Analysis with Statistics and Machine Learning. Data Communication with Information Visualization. 


Python is a high-level programming language designed to be easy to read and simple to install. It is open source, which means it is free to use, even for commercial applications. Python can run on Mac, Windows, and Unix systems and has also ported to Java and .NET virtual machines. 


These are the basic libraries that transform Python from general purpose programming language  into powerful. Robust tool for data analysis and visualization. Sometimes called the SciPy Stack.

  1. NumPy is the foundational library for scientific computing in Python. Many of libraries on this list use NumPy arrays as their basic inputs and outputs. In short, NumPy introduces objects for multi-dimensional arrays and matrices.
  2. 2. SciPy builds on NumPy by adding collection of algorithms and high-level commands for manipulating and visualizing data. This package includes functions for computing integrals , solving differential equations.
  3. 3.Pandas add data structures and tools that are designed for practical data analysis infinance,statistics, social sciences, and engineering. Panda’s works well with incomplete, messy.
  4. 4.IPython extends the functionality of Python interactive interpreter with souped-up interactive shell that adds introspection. It also acts as embedded interpreter for your programs that can be useful .
  5. 5.Matplotlib is standard Python library for creating 2D plots and graphs. It’s pretty low level, meaning it requires more commands to generate nice-looking graphs. 


1.scikit learn builds on NumPy and SciPy by adding set of algorithms for common machine learning. Data mining tasks, including clustering, regression, and classification.

2. Theano uses NumPy-like syntax to optimize and test mathematical expressions. What sets Theano apart is that it takes advantage of computer GPU to make data intensive calculations to 100 xs faster than the CPU alone.

3. TensorFlow is another high-profile entrant into machine learning, developed by Google as an open- source successor to DistBelief, their previous framework for training neural networks.


Imagine scenario in which your business does not have the advantage of getting to gigantic datasets. 

1.Scrapy is an named library for creating spider bots to crawl the web and extract structured data like prices, contact info, and URLs.

2. NLTK is set of libraries designed for Natural Language Processing. NLTK basic functions allow you to tag text, identify named entities, and display parse trees. which are like sentence diagrams that reveal parts of speech and dependencies.

3. Pattern combines the functionality of Scrappy and NLTK in a massive library designed to serve as out of box solution for web mining, NLP, machine learning, and network analysis.


The best and most sophisticated analysis is meaningless if you cannot communicate it to other people. 

  1. Seaborn is a popular visualization library that builds on matplotlib’s foundation.
  2. 2.Bokeh makes interactive, zoom able plots in modern web browsers using JavaScript widgets.
  3. 3. Basemap adds support for simple maps to matplotlib by taking matplotlib’s coordinates
  4. 4. NetworkXformats.Data science training in kukatpally