100Daysof DScode (Datascience) Day 2-Python for Data science

Kindly see the curriculum and topic for each week https://gist.github.com/Emekaborisama/c172599855a757b624c783c9a64ebd0c

100daysofdscode

In our day 1, we did a brief introduction to Data Science, Python for Data Science and Why Data Scientist uses Python.

Today we are going to learn about:

1. Market Potential for Python
2. 5 industries that make effective use of their data, and how!
3. OOP (object-oriented programming)

Let’s Fly with Emirate Air

Market Potential for Python

According to Kgnugget, 46% of all Data Science job requires knowledge of python.

ACM says that python has overtaken Java in the U.S academic and industry.

IBM Predicts Demand For Data Scientists Will Soar 28% By 2020.

As we all know data science is now the talk of the day and the new oil that will propel the technology industry, a lot of organization has predicted and taken a bold step toward employing data scientist or consulting a data scientist to see how meaningful value can be derived from data collected.

Assignment 101 find how data science is being used at an organisation close to you.

5 industries that make effective use of their data, and how!

1. Banking: The banking sector is continuously at the pool of fraudulent practices, curbing Malpractices and poor customer experience. Data Science has helped the banking industry improve in their customer services such as detecting customer churn, detecting fraudulent activities and monitoring financial markets and network analysis to detect curbing malpractices
2. E-Commerce: Cross-selling, re-marketing, packaged services, recommendation, customized offers, or personalized products; the additions brought by Data Science to the e-commerce industry are endless. Customer data is being hounded like never before, and recommendations are hurled on them from all direction possible, depending upon their buying patterns, search histories, and behavioral analysis.
3. Health: For an industry suffering from unusable data and rising costs, Data Science appears as an obvious rescue. Apart from helping analyze a large amount of genomic data, it enables leveraging public health data and processing records of past treatments. Coupled with effective use of technology, it further helps in conducting predictive analysis, identifying chronic disease trends, offering personalized treatments, and eventually slashing costs.
4. Telecoms: Data Scientists of the telecom industry spend a lot of time creating sophisticated 360-degree customer profiles. Using demographic as well as behavioral data, the companies are able to strike the chords with their customers. They are also able to optimize their individual network solutions.
5. Travel and Tourism: Almost every other industry is using customer data for personalized product offering. However, travel takes it further to an ultra-personalized product and service offering. In-depth 360-degree view of the customers, as well as a multi-layered data analysis across touch-points, helps the companies identify most-valuable customers, cross-sell partner products, and advance highly customized products and services to its customers.

Recommended articles

1. Democratization of Data Science
2. The Kind of Data Science

OOP (object-oriented programming)

(This is a brief introduction to Object Oriented programming)

OOP is a methodology that is object-oriented, it focuses more on object than function and procedures. OOP makes it easier for programmers to design and structure software programs.

In conclusion, we have been able to understand the Market potential for Python, Industries that make effective use of their data and object-oriented programming.

Kindly share your progress on your social media page

(A sample)

Day 2: Market potential, Industries that make effective use of their data and object-oriented programming.

Day 2 Lesson: At the end of today’s session i learned the Market potential for Python, Industries that make effective use of their data and object-oriented programming.

Don’t forget to use the hashtag #100daysofcode #100daysofDscode #100days #Day2 #Day2outof100 #DataScience #MachineLearning #Ai

THANKS AND SEE YOU IN DAY 3.