DATA SCIENCE WITH PYTHON

EMMANUEL ORAMAH

Emmanuel Oramah is an MSc. holder in Polymer Science. He, however, has a strong background in ICT based programs. His majors includes Graphics Designing, front end and back end Web Programming, Data Science and Software Management. He is the chief consultant with MadoniMatrix Global Concepts, an ICT and industrial consultancy establishment, registered with the CAC. He also undertakes online/offline private tutorials if contracted. He is also a published author of 4 inspirational books. He fears God and loves people.

ABOUT THE COURSE

Python programming language is an open source programming language that is being used for very many applications; ranging from software development, website development, data science, machine learning, artificial intelligence

This data science with Python tutorial will help you learn the basics of Python along with different steps of data science such as data preprocessing, data visualization, statistics, and much more with the help of detailed and well-explained examples. This tutorial will help both beginners as well as some trained professionals in mastering data science with Python.

Data Science is relevant today because we have millions of data available on single data or for single data. We didn’t use to worry about the lack of data. Now we have tons of data. In the past, we didn’t have defined algorithms, now we have algorithms. In the past, the software was not affordable by everyone because it was too expensive, so only industries with big-bucks can use it but now it is open source and freely available. In the past, we didn’t even think about storing a large amount of data, because the storage facilities are also very costly and now it is available for a fraction of a cost, we can have gazillions of data sets for a very low cost. Also, internet connectivity was not common and too costly. So, the tools to work with data, the variability of data, the ability to store, analyze data and last and most important Connectivity, it’s all cheap, it’s all available, it’s all ubiquitous, it’s here. There’s never been a better time to be a data scientist than now.

APPLICATIONS OF DATA SCIENCE:

Following are some of the applications that make use of Data Science for their services:

• Recommendation Engine (Spotify)

• Intelligent Digital Assistants (Google Assistant)

• Abusive Content and Hate Speech Filter (Facebook)

• Robotics (Boston Dynamics)

ADVANTAGES OF DATA SCIENCE 

There are many advantages of using data science in various industries and applications. Some of the key advantages include:

1. Automation: Data science can be used to automate repetitive tasks, such as data cleaning, feature engineering, and model selection, which can save time and resources.

2. Cost reduction: Data science can be used to identify inefficiencies and reduce costs in various industries, such as supply chain management and healthcare.

3. Fraud Detection: Data science can be used to analyze large amounts of transaction data and identify fraudulent activities, which can reduce financial losses.

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