The Data Science Pro Bootcamp 2022: 75 Projects In 75 Days
The 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.
In This Course, We Are Going To Work On 75 Real World Data Science, Machine Learning 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: Language Translator App Using IBM Cloud Service -Deploy On Heroku
Project-12: Predict Views On Advertisement Using IBM Watson -Deploy On Heroku
Project-13: Laptop Price Predictor -Deploy On Heroku
Project-14: WhatsApp Text Analyzer -Deploy On Heroku
Project-15: Course Recommendation System -Deploy On Heroku
Project-16: IPL Match Win Predictor -Deploy On Heroku
Project-17: Body Fat Estimator App -Deploy On Microsoft Azure
Project-18: Campus Placement Predictor App -Deploy On Microsoft Azure
Project-19: Car Acceptability Predictor -Deploy On Google Cloud
Project-20: Book Genre Classification App -Deploy On Amazon Web Services
Project 21 : DNA classification Deep Learning for finding E.Coli -AWS - Deploy On AWS
Project 22 : Predict the next word in a sentence. - AWS - Deploy On AWS
Project 23 : Predict Next Sequence of numbers using LSTM - AWS - Deploy On AWS
Project 24 : Keyword Extraction from text using NLP - Deploy On Azure
Project 25 : Correcting wrong spellings (correct spelling prediction) - Deploy On Azure
Project 26 : Music popularity classififcation - Deploy On Google App Engine
Project 27 : Advertisement Classification - Deploy On Google App Engine
Project 28 : Image Digit Classification - Deploy On AWS
Project 29 : Emotion Recognition using Neural Network - Deploy On AWS
Project 30 : Breast cancer Classification - Deploy On AWS
Project-31: Sentiment Analysis Django App -Deploy On Heroku
Project-32: Attrition Rate Django Application
Project-33: Find Legendary Pokemon Django App -Deploy On Heroku
Project-34: Face Detection Streamlit App
Project-35: Cats Vs Dogs Classification Flask App
Project-36: Customer Revenue Prediction App -Deploy On Heroku
Project-37: Gender From Voice Prediction App -Deploy On Heroku
Project-38: Restaurant Recommendation System
Project-39: Happiness Ranking Django App -Deploy On Heroku
Project-40: Forest Fire Prediction Django App -Deploy On Heroku
Project-41: Build Car Prices Prediction App -Deploy On Heroku
Project-42: Build Affair Count Django App -Deploy On Heroku
Project-43: Build Shrooming Predictions App -Deploy On Heroku
Project-44: Google Play App Rating prediction With Deployment On Heroku
Project-45: Build Bank Customers Predictions Django App -Deploy On Heroku
Project-46: Build Artist Sculpture Cost Prediction Django App -Deploy On Heroku
Project-47: Build Medical Cost Predictions Django App -Deploy On Heroku
Project-48: Phishing Webpages Classification Django App -Deploy On Heroku
Project-49: Clothing Fit-Size predictions Django App -Deploy On Heroku
Project-50: Build Similarity In-Text Django App -Deploy On Heroku
Project-51 : Sonic wave velocity prediction using Signal Processing Techniques
Project-52 : Estimation of Pore Pressure using Machine Learning
Project-53 : Audio processing using ML
Project-54 : Text characterisation using Speech recognition
Project-55 : Audio classification using Neural networks
Project-56 : Developing a voice assistant
Project-57 : Customer segmentation
Project-58 : FIFA 2019 Analysis
Project-59 : Sentiment analysis of web scrapped data
Project-60 : Determing Red Vine Quality
Project-61: Heart Attack Risk Prediction Using Eval ML (Auto ML)
Project-62: Credit Card Fraud Detection Using Pycaret (Auto ML)
Project-63: Flight Fare Prediction Using Auto SK Learn (Auto ML)
Project-64: Petrol Price Forecasting Using Auto Keras
Project-65: Bank Customer Churn Prediction Using H2O Auto ML
Project-66: Air Quality Index Predictor Using TPOT With End-To-End Deployment (Auto ML)
Project-67: Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)
Project-68: Pizza Price Prediction Using ML And EVALML(Auto ML)
Project-69: IPL Cricket Score Prediction Using TPOT (Auto ML)
Project-70: Predicting Bike Rentals Count Using ML And H2O Auto ML
Project-71: Concrete Compressive Strength Prediction Using Auto Keras (Auto ML)
Project-72: Bangalore House Price Prediction Using Auto SK Learn (Auto ML)
Project-73: Hospital Mortality Prediction Using PyCaret (Auto ML)
Project-74: Employee Evaluation For Promotion Using ML And Eval Auto ML
Project-75: Drinking Water Potability Prediction Using ML And H2O Auto ML
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.
Build 75 Projects in 75 Days- Data Science, Machine Learning, Deep Learning (Python, Flask, Django, AWS, Heruko Cloud)
Url: View Details
What you will learn
- Conduct feature engineering on real world case studies.
- Learn how to improve your Machine Learning Models
- Have a great intuition of many Machine Learning models
![](https://img-c.udemycdn.com/course/240x135/4889472_8441_2.jpg)
Rating: 4.82143
Level: All Levels
Duration: 73.5 hours
Instructor: Pianalytix .
Courses By: 0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
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