Python Data Science Course And Certification

What is Python Data Science?

Python Data Science is the use of Python Programming Language with scientific algorithms and methods to process data. 

What is Data Science?

Data Science is simply the use of scientific methods and algorithms to process data.  

What is Python?

Python is an open-source, interpreted, high-level, and object-oriented programming language. It is one of the best language that is used by data scientists for various data science applications/projects. Python comes with a lot of great functionalities to handle mathematics, statistics, and scientific functions. It also offers awesome libraries that deals with data science applications.

One of the main reasons why Python is broadly used in the scientific and research communities is because of its ease of use and very simple syntax that makes it easy to adapt for people that do not have an engineering background. It is also more suited for quick prototyping.

According to engineers that are coming from academia and industry, deep learning frameworks are made available with Python APIs, together with the scientific packages that have made Python incredibly productive and versatile. There has been a lot of evolution in deep learning Python frameworks and it is rapidly upgrading.

In the areas of application development, ML scientists prefer Python as well. When it comes to areas of developing fraud detection algorithms and network security tools, developers usually prefer to use Java, while for applications like natural language processing (NLP) and sentiment analysis, developers usually go for Python, because it provides a large collection of libraries that help to solve the complex business problem very easy, build strong system and data application tools.

Features Of Python for Data Science

1. It uses the elegant syntax, hence the programs are easier to read.

2. It is a simple to access language, which makes it easy to achieve the program working.

3. The large standard library and community support.

4. The interactive mode of Python makes it simple to test codes.

5. In Python, it is also simple to extend the code by appending new modules that are implemented in other compiled languages like C++ or C.

6. Python is an expressive language that is possible to embed into applications to offer a programmable interface.

7. Allows the developer to run the code anywhere, including Windows, Mac OS X, UNIX, and Linux.

8. It is free software in a couple of categories. It does not cost anything to use or download Pythons or to add it to the application. 

Data Science Libraries

Most commonly used libraries for data science: 

1. Numpy: Numpy is a Python library that provides the mathematical functions to handle large dimension array.
2. Pandas: Pandas is one of the very popular Python libraries that is used for data manipulation and analysis.
3. Matplotlib: Matplolib is another very useful Python library that is used for Data Visualization.
4. Scipy: Scipy is another very popular Python library that is used for data science and for scientific computing purposes.
5. Scikit – learn: Sklearn is a Python library that is used for machine learning.

Benefits of Python For Data Science

Some of the many benefits of Python Data Science include: 

1. Open-source and free.
2. Easy to learn.
3. Fewer lines of code.
4. Portability.
5. Better productivity.
6. Demand and popularity.
7. Excellent online presence/ community.
8. Python has support for many packages that are usable with analytics projects.
9. It is faster than similar tools such as MATLAB or R.
10. Amazing memory management abilities.

Why Study Python Data Science

1. Increase Your Knowledge on Data Science.
2. Job Opportunities and Career Advancement.
3. Increase Your Earning Potential.
4. Become a Data Science Professional.
5. Be in Demand and Command High Pay.
6. Self-Employment Opportunities and Consultancy.

Python Data Science Course Outline: 

Python Data Science - Introduction

Python Data Science - Discovering the Match between Data Science and Python

Python Data Science - Introducing Python Capabilities

Python Data Science - Setting Up Python for Data Science

Python Data Science - Reviewing Basic Python

Python Data Science - Working with Real Data

Python Data Science - Conditioning Data

Python Data Science - Shaping the Data

Python Data Science - Putting What You Know in Action

Python Data Science - MatPlotLib

Python Data Science - Visualizing the Data

Python Data Science - Understanding the Tools

Python Data Science - Stretching Python Capabilities

Python Data Science - Exploring Data Analysis

Python Data Science - Reducing Dimensionality

Python Data Science - Clustering

Python Data Science - Detecting Outliers in Data

Python Data Science - Exploring Four Simple and Effective Algorithms

Python Data Science - Performing Cross-Validation, Selection and Optimization

Python Data Science - Increasing Complexity with Linear and Nonlinear Tricks

Python Data Science - Understanding the Power of the Many

Python Data Science - Essential Data Science Resource Collections

Python Data Science - Data Challenges You Should Take

Python Data Science - Video Lectures

Python Data Science - Exams and Certification