Data Science Mega-Course: #Build {120-Projects In 120-Days}
Data Science Mega-Course: #Build {120-Projects In 120-Days}
In This Course, Solve Business Problems Using Data Science Practically. Learn To Build & Deploy Machine Learning, Data Science, Artificial Intelligence
Go Link On Udemy
You'll learn Data Science Mega-Course: #Build {120-Projects In 120-Days}
- Make powerful analysis, Make robust Machine Learning models
- Master Machine Learning on Python
- Know which Machine Learning model to choose for each type of problem
- Implement Machine Learning Algorithms
- Explore how to deploy your machine learning models.
- Understand the full product workflow for the machine learning lifecycle.
- Present Data Science projects to management
- Real life case studies and projects to understand how things are done in the real world
- Build a portfolio of work to have on your resume
Welcome On Udemy Course Data Science Mega-Course: #Build {120-Projects In 120-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).
According to Glassdoor, the average salary for a Data Scientist is $117,345/yr. This is above the national average of $44,564. Therefore, a Data Scientist makes 163% more than the national average salary.
This makes Data Science a highly lucrative career choice. It is mainly due to the dearth of Data Scientists resulting in a huge income bubble.
Since Data Science requires a person to be proficient and knowledgeable in several fields like Statistics, Mathematics, and Computer Science, the learning curve is quite steep. Therefore, the value of a Data Scientist is very high in the market.
A Data Scientist enjoys a position of prestige in the company. The company relies on its expertise to make data-driven decisions and enable them to navigate in the right direction.
Furthermore, the role of a Data Scientist depends on the specialization of his employer company. For example – A commercial industry will require a data scientist to analyze their sales.
A healthcare company will require data scientists to help them analyze genomic sequences. The salary of a Data Scientist depends on his role and type of work he has to perform. It also depends on the size of the company which is based on the amount of data they utilize.
Still, the pay scale of Data scientists is way above other IT and management sectors. However, the salary observed by Data Scientists is proportional to the amount of work that they must put in. Data Science needs hard work and requires a person to be thorough with his/her skills.
Due to several lucrative perks, Data Science is an attractive field. This, combined with the number of vacancies in Data Science makes it an untouched gold mine. Therefore, you should learn Data Science in order to enjoy a fruitful career.
In This Course, We Are Going To Work On 120 Real World Projects Listed Below:
- Project-1: Pan Card Tempering Detector App -Deploy On Heroku
- Project-2: Dog breed prediction Flask App
- Project-3: Image Watermarking App -Deploy On Heroku
- Project-4: Traffic sign classification
- Project-5: Text Extraction From Images Application
- Project-6: Plant Disease Prediction Streamlit App
- Project-7: Vehicle Detection And Counting Flask App
- Project-8: Create A Face Swapping Flask App
- Project-9: Bird Species Prediction Flask App
- Project-10: Intel Image Classification Flask App
