Data Science Mega-Course: #Build {60-Projects In 60-Days}

Learn To Build & Deploy Data Science, ML, Deep Learning Projects (Python, Flask, Django, AWS, Azure, GCP, Heruko Cloud)

What you’ll learn
Understand the full product workflow for the machine learning lifecycle.
Master Machine Learning on Python
Have a great intuition of many Machine Learning models
Make robust Machine Learning models
Real life case studies and projects to understand how things are done in the real world
Learn best practices when it comes to Data Science Workflow
Build a portfolio of work to have on your resume

Description
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 60 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

Project-11: Sentiment Analysis Django App -Deploy On Heroku

Project-12: Attrition Rate Django Application

Project-13: Find Legendary Pokemon Django App -Deploy On Heroku

Project-14: Face Detection Streamlit App

Project-15: Cats Vs Dogs Classification Flask App

Project-16: Customer Revenue Prediction App -Deploy On Heroku

Project-17: Gender From Voice Prediction App -Deploy On Heroku

Project-18: Restaurant Recommendation System

Project-19: Happiness Ranking Django App -Deploy On Heroku

Project-20: Forest Fire Prediction Django App -Deploy On Heroku

Project-21: Build Car Prices Prediction App -Deploy On Heroku

Project-22: Build Affair Count Django App -Deploy On Heroku

Project-23: Build Shrooming Predictions App -Deploy On Heroku

Project-24: Google Play App Rating prediction With Deployment On Heroku

Project-25: Build Bank Customers Predictions Django App -Deploy On Heroku

Project-26: Build Artist Sculpture Cost Prediction Django App -Deploy On Heroku

Project-27: Build Medical Cost Predictions Django App -Deploy On Heroku

Project-28: Phishing Webpages Classification Django App -Deploy On Heroku

Project-29: Clothing Fit-Size predictions Django App -Deploy On Heroku

Project-30: Build Similarity In-Text Django App -Deploy On Heroku

Project-31: Heart Attack Risk Prediction Using Eval ML (Auto ML)

Project-32: Credit Card Fraud Detection Using Pycaret (Auto ML)

Project-33: Flight Fare Prediction Using Auto SK Learn (Auto ML)

Project-34: Petrol Price Forecasting Using Auto Keras

Project-35: Bank Customer Churn Prediction Using H2O Auto ML

Project-36: Air Quality Index Predictor Using TPOT With End-To-End Deployment (Auto ML)

Project-37: Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)

Project-38: Pizza Price Prediction Using ML And EVALML(Auto ML)

Project-39: IPL Cricket Score Prediction Using TPOT (Auto ML)

Project-40: Predicting Bike Rentals Count Using ML And H2O Auto ML

Project-41: Concrete Compressive Strength Prediction Using Auto Keras (Auto ML)

Project-42: Bangalore House Price Prediction Using Auto SK Learn (Auto ML)

Project-43: Hospital Mortality Prediction Using PyCaret (Auto ML)

Project-44: Employee Evaluation For Promotion Using ML And Eval Auto ML

Project-45: Drinking Water Potability Prediction Using ML And H2O Auto ML

Project-46: Black Friday Sale Project

Project-47: Sentiment Analysis Project

Project-48: Parkinson’s Disease Prediction Project

Project-49: Fake News Classifier Project

Project-50: Toxic Comment Classifier Project

Project-51: Language Translator App Using IBM Cloud Service -Deploy On Heroku

Project-52: Predict Views On Advertisement Using IBM Watson -Deploy On Heroku

Project-53: Laptop Price Predictor -Deploy On Heroku

Project-54: WhatsApp Text Analyzer -Deploy On Heroku

Project-55: Course Recommendation System -Deploy On Heroku

Project-56: IPL Match Win Predictor -Deploy On Heroku

Project-57: Body Fat Estimator App -Deploy On Microsoft Azure

Project-58: Campus Placement Predictor App -Deploy On Microsoft Azure

Project-59: Car Acceptability Predictor -Deploy On Google Cloud

Project-60: Book Genre Classification App -Deploy On Amazon Web Services

Tip: Create A 60 Days Study Plan, Spend 1-2hrs Per Day, Build 60 Projects In 60 Days.

The Only Course You Need To Become A Data Scientist, Get Hired And Start A New Career

Note (Read This): This Course Is Worth Of Your Time And Money, Enroll Now Before Offer Expires.

Who this course is for:
Anyone who is beginner in data science.
Beginner Python developers curious about Machine Learning and Data Science with Python

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