Udemy

50-Days 50-Projects: Data Science, Machine Learning Bootcamp

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  • 1,765 Students
  • Updated 10/2025
  • Certificate Available
4.2
(129 Ratings)
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Course Information

Registration period
Year-round Recruitment
Course Level
Study Mode
Language
English
Taught by
Pianalytix • 75,000+ Students Worldwide
Certificate
  • Available
  • *The delivery and distribution of the certificate are subject to the policies and arrangements of the course provider.
Rating
4.2
(129 Ratings)
4 views

Course Overview

50-Days 50-Projects: Data Science, Machine Learning Bootcamp

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

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).

Data science can be defined as a blend of mathematics, business acumen, tools, algorithms, and machine learning techniques, all of which help us in finding out the hidden insights or patterns from raw data which can be of major use in the formation of big business decisions.

In data science, one deals with both structured and unstructured data. The algorithms also involve predictive analytics. Thus, data science is all about the present and future. That is, finding out the trends based on historical data which can be useful for present decisions, and finding patterns that can be modeled and can be used for predictions to see what things may look like in the future.

Data Science is an amalgamation of Statistics, Tools, and Business knowledge. So, it becomes imperative for a Data Scientist to have good knowledge and understanding of these.

With the amount of data that is being generated and the evolution in the field of Analytics, Data Science has turned out to be a necessity for companies. To make the most out of their data, companies from all domains, be it Finance, Marketing, Retail, IT or Bank. All are looking for Data Scientists. This has led to a huge demand for Data Scientists all over the globe. With the kind of salary that a company has to offer and IBM is declaring it as the trending job of the 21st century, it is a lucrative job for many. This field is such that anyone from any background can make a career as a Data Scientist.

In This Course, We Are Going To Work On 50 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: 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: Sentiment Analysis Django App -Deploy On Heroku

Project-22: Attrition Rate Django Application

Project-23: Find Legendary Pokemon Django App -Deploy On Heroku

Project-24: Face Detection Streamlit App

Project-25: Cats Vs Dogs Classification Flask App

Project-26: Customer Revenue Prediction App -Deploy On Heroku

Project-27: Gender From Voice Prediction App -Deploy On Heroku

Project-28: Restaurant Recommendation System

Project-29: Happiness Ranking Django App -Deploy On Heroku

Project-30: Forest Fire Prediction Django App -Deploy On Heroku


Project-31: Build Car Prices Prediction App -Deploy On Heroku

Project-32: Build Affair Count Django App -Deploy On Heroku

Project-33: Build Shrooming Predictions App -Deploy On Heroku

Project-34: Google Play App Rating prediction With Deployment On Heroku

Project-35: Build Bank Customers Predictions Django App -Deploy On Heroku

Project-36: Build Artist Sculpture Cost Prediction Django App -Deploy On Heroku

Project-37: Build Medical Cost Predictions Django App -Deploy On Heroku

Project-38: Phishing Webpages Classification Django App -Deploy On Heroku

Project-39: Clothing Fit-Size predictions Django App -Deploy On Heroku

Project-40: Build Similarity In-Text Django App -Deploy On Heroku


Project-41: Heart Attack Risk Prediction Using Eval ML (Auto ML)

Project-42: Credit Card Fraud Detection Using Pycaret (Auto ML)

Project-43: Flight Fare Prediction Using Auto SK Learn (Auto ML)

Project-44: Petrol Price Forecasting Using Auto Keras

Project-45: Bank Customer Churn Prediction Using H2O Auto ML

Project-46: Air Quality Index Predictor Using TPOT With End-To-End Deployment (Auto ML)

Project-47: Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)

Project-48: Pizza Price Prediction Using ML And EVALML(Auto ML)

Project-49: IPL Cricket Score Prediction Using TPOT (Auto ML)

Project-50: Predicting Bike Rentals Count Using ML And H2O Auto ML


Tip: Create A 50 Days Study Plan, Spend 1-2hrs Per Day, Build 50 Projects In 50 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.

Course Content

  • 51 section(s)
  • 367 lecture(s)
  • Section 1 Introduction To The Course
  • Section 2 Project-1: Pan Card Tempering Detector App -Deploy On Heroku
  • Section 3 Project-2: Dog breed prediction Flask App
  • Section 4 Project-3: Image Watermarking App -Deploy On Heroku
  • Section 5 Project-4: Traffic sign classification
  • Section 6 Project-5: Text Extraction From Images Application
  • Section 7 Project-6: Project On Plant Disease Prediction
  • Section 8 Project-7: Vehicle Detection And Counting
  • Section 9 Project-8: Create A Face Swap Application
  • Section 10 Project-9: Bird Species Prediction Flask App
  • Section 11 Project-10: Intel Image Classification Flask App
  • Section 12 Project-11: Language Translator App Using IBM Cloud Service -Deploy On Heroku
  • Section 13 Project-12: Predict Views On Advertisement Using IBM Watson -Deploy On Heroku
  • Section 14 Project-13: Laptop Price Predictor -Deploy On Heroku
  • Section 15 Project-14: WhatsApp Text Analyzer -Deploy On Heroku
  • Section 16 Project-15: Course Recommendation System -Deploy On Heroku
  • Section 17 Project-16: IPL Match Win Predictor -Deploy On Heroku
  • Section 18 Project-17: Body Fat Estimator App -Deploy On Microsoft Azure
  • Section 19 Project-18: Campus Placement Predictor App -Deploy On Microsoft Azure
  • Section 20 Project-19: Car Acceptability Predictor -Deploy On Google Cloud
  • Section 21 Project-20: Book Genre Classification App -Deploy On Amazon Web Services
  • Section 22 Project-21: Sentiment Analysis Django App -Deploy On Heroku
  • Section 23 Project-22: Attrition Rate Django Application
  • Section 24 Project-23: Find Legendary Pokemon Django App -Deploy On Heroku
  • Section 25 Project-24: Face Detection Streamlit App
  • Section 26 Project-25: Cats Vs Dogs Classification Flask App
  • Section 27 Project-26: Customer Revenue Prediction App -Deploy On Heroku
  • Section 28 Project-27: Gender From Voice Prediction App -Deploy On Heroku
  • Section 29 Project-28: Restaurant Recommendation System
  • Section 30 Project-29: Happiness Ranking Django App -Deploy On Heroku
  • Section 31 Project-30: Forest Fire Prediction Django App -Deploy On Heroku
  • Section 32 Project-31: Build Car Prices Prediction App -Deploy On Heroku
  • Section 33 Project-32: Build Affair Count Django App -Deploy On Heroku
  • Section 34 Project-33: Build Shrooming Predictions App -Deploy On Heroku
  • Section 35 Project-34: Google Play App Rating prediction With Deployment On Heroku
  • Section 36 Project-35: Build Bank Customers Predictions Django App -Deploy On Heroku
  • Section 37 Project-36: Build Artist Sculpture Cost Prediction Django App -Deploy On Heroku
  • Section 38 Project-37: Build Medical Cost Predictions Django App -Deploy On Heroku
  • Section 39 Project-38: Phishing Webpages Classification Django App -Deploy On Heroku
  • Section 40 Project-39: Clothing Fit-Size predictions Django App -Deploy On Heroku
  • Section 41 Project-40: Build Similarity In-Text Django App -Deploy On Heroku
  • Section 42 Project-41: Heart Attack Risk Prediction Using Eval ML (Auto ML)
  • Section 43 Project-42: Credit Card Fraud Detection Using Pycaret (Auto ML)
  • Section 44 Project-43: Flight Fare Prediction Using Auto SK Learn (Auto ML)
  • Section 45 Project-44: Petrol Price Forecasting Using Auto Keras
  • Section 46 Project-45: Bank Customer Churn Prediction Using H2O Auto ML
  • Section 47 Project-46: Air Quality Index Predictor Using TPOT With Deployment (Auto ML)
  • Section 48 Project-47: Rain Prediction Using ML models & PyCaret With Deployment (Auto ML)
  • Section 49 Project-48: Pizza Price Prediction Using ML And EVALML(Auto ML)
  • Section 50 Project-49: IPL Cricket Score Prediction Using TPOT (Auto ML)
  • Section 51 Project-50: Predicting Bike Rentals Count Using ML And H2O Auto ML

What You’ll Learn

  • Make robust Machine Learning models
  • Understand the full product workflow for the machine learning lifecycle.
  • Real life case studies and projects to understand how things are done in the real world
  • Know which Machine Learning model to choose for each type of problem
  • Learn how to program in Python using the latest Python 3
  • Learn to pre process data, clean data, and analyze large data
  • Learn to use NumPy for Numerical Data
  • Learn to use Pandas for Data Analysis
  • Have a great intuition of many Machine Learning models


Reviews

  • J
    Joao Victor Barbosa
    4.0

    The accent is hard to understand

  • K
    K Santosh Kumar
    3.0

    ok

  • B
    Biswajit Gochhayat
    1.0

    as per your advertisement, i think you are going to give me an end to end project developments with proper explanation..so I am not satisfied with it.

  • M
    Manuel
    2.0

    Topics are explained with an extreme rush. Only one question was answered by the author on the F&Q. If you know well all the topics you may find the course somehow useful, otherwise refrain from buying this course

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