The Data Science Pro Bootcamp 2022: 75 Projects In 75 Days
The Data Science Pro Bootcamp 2022: 75 Projects In 75 Days
Build 75 Projects in 75 Days- Data Science, Machine Learning, Deep Learning (Python, Flask, Django, AWS, Heruko Cloud)
What you'll learn
- Conduct feature engineering on real world case studies.
- How to improve your Machine Learning Models
- Beginner Friendly Projects
- Learn best practices for real-world data sets.
About The Course : Data Science Pro Bootcamp 2022: 75 Projects In 75 Days
In This Course, Solve Business Problems Using Data Science Practically. Learn To Build & Deploy Machine Learning, Data Science, Artificial Intelligence, Auto Ml, Deep Learning, Natural Language Processing (Nlp) Web Applications Projects With Python (Flask, Django, Heroku, AWS, Azure, GCP, IBM Watson, Streamlit Cloud).
In the last century, oil was considered as the ‘black gold’. But, with the industrial revolution and the emergence of the automotive industry, oil became the main driving source of human civilization.
However, with time, its value dwindled due to the gradual exhaustion and resorting to alternative renewable sources of energy.
In the 21st century, the new driving force behind industries is Data. As a matter of fact, even automobile industries are using data to impart autonomy and improve the safety of their vehicles. The idea is to create powerful machines that think in the form of data.
Data Science is also the electricity that powers the industries of today. Industries need data to improve their performance, make their business grow and provide better products to their customers.
In the scenario of data science section, we took an example of a commercial industry that wants to maximize its sales.
In order to do so, it requires a thorough analysis of data behind sales, understanding of the purchasing patterns of the clients and using their suggestions to improve the product. To perform all these tasks, a Data Scientist is required.
Similarly, take an example of a Business Intelligence company is required to analyze its potential customers base. It requires a Data Scientist to utilize the data they breathe on the internet to track their daily trends and analyze their behavioral patterns.
A Data Scientist will use his tools to sculpt through all this data and chisel out meaningful observations that will help companies to make profound decisions.
Similarly, a health-care company specializing in building conversational platforms for patients of mental health will need data to analyze the trends and patterns. Automobile industries need data to develop self-driving cars.
Data is being generated since the dawn of human civilization. However, only recently we have been able to tap its true potential and draw insights from it. Only in the past decade, we have started to depict data as a fuel for industries. The main contributor to this latest revolution is the rise in computational power.
