- Introduction To The Course
- Course Outline Video
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Data Science Mega-Course: #Build {60-Projects In 60-Days}
Learn how to create and deliver data science, machine learning, and deep learning applications using Python, Flask, Django, Azure, GCP, AWS, and Heroku cloud.
Beginner
Online
₹ 479 1,299
Quick facts
particular | details | |
---|---|---|
Medium of instructions
English
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Mode of learning
Self study
|
Mode of Delivery
Video and Text Based
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Course overview
Pianalytix, a Technology learning provider, developed the Data Science Mega-Course: #Build 60-Projects In 60-Days online certification, which is presented by Udemy and is aimed at individuals who wish to expand their abilities in the data science field. The Data Science Mega-Course: #Build60-ProjectsIn60-Days online course by Udemy teaches the core concepts of artificial intelligence, machine learning, deep learning, and natural language processing, among other technologies and topics in data science.
Data Science Mega-Course: #Build {60-Projects In 60-Days} online classes are designed to provide students with a practical understanding of data science principles and methodologies, and this course includes 60 projects that cover a variety of topics, both fundamental and advanced. This course also covers several cloud platforms so that students may design data science projects and deploy them on AWS, Google Cloud, Heroku, IBM Watson, Streamlit cloud, and Azure.
The highlights
- Certificate of completion
- Self-paced course
- 52 hours of pre-recorded video content
- 60 articles
- 70 downloadable resources
- Projects
Program offerings
- Online course
- Projects
- 30-day money-back guarantee
- Unlimited access
- Accessible on mobile devices and tv
Course and certificate fees
Fees information
certificate availability
certificate providing authority
What you will learn
After completing the Data Science Mega-Course: #Build {60-Projects In 60-Days} certification course, individuals will obtain a thorough understanding of data science's fundamental principles. Individuals will explore the fundamentals of artificial intelligence, machine learning, deep learning, and natural language processing. Individuals will gain a thorough grasp of numerous data science tools such as Python and Django, as well as several cloud platforms for deploying applications such as AWS, Google Cloud, Heroku, IBM Watson, Straeamlit cloud, and Microsoft Azure.
Who it is for
The syllabus
Introduction To The Course
Project-1: Pan Card Tempering Detector App -Deploy On Heroku
- Introduction To Pan Card Tempering Detector
- Loading libraries and dataset
- Creating the pancard detector with opencv
- Creating the Flask App
- Creating Important functions
- Deploy the app in heroku
- Testing the deployed pan card detector
- Download The Project Files
Project-2: Dog breed prediction Flask App
- Introduction to dog breed prediction
- Importing the data and libraries
- Data Preprocessing
- Build and Train Model
- Testing the model
- Creating the flask App
- Running the app in system
- Download The Project Files
Project-3: Image Watermarking App -Deploy On Heroku
- Introduction
- Importing libraries and logo
- Create text and image watermark
- Creating the app
- Deploying the app in heroku
- Download the project files
Project-4: Traffic sign classification
- Introduction to traffic sign classification
- Importing the data and libraries
- Image processing
- Creating and testing the model
- Creating model for test set
- Download the project files
Project-5: Project on text extraction from images
- Introduction to text extraction
- Importing libraries and data
- Extracting the test from image
- Modifying the extractor
- Creating the extractor app
- Running the extractor app
- Download The Project Files
Project-6: Plant Disease Prediction Streamlit App
- Introduction -Plant Disease Prediction Streamlit App
- Importing libraries and data
- Understanding the data and data preprocessing
- Model building
- Creating an app using streamlit
- Download The Project Files
Project-7: Vehicle Detection And Counting Flask App
- Introduction
- Importing libraries and data
- Transforming Images and creating output
- Creating a flask App
- Download The Project Files
Project-8: Create A Face Swapping Flask App
- Introduction
- Importing libraries and data
- Data preprocessing and creating output
- Creating A Flask App
- Download The Project Files
Project-9: Bird Species Prediction Flask App
- Introduction to Bird Species Prediction
- Importing Libraries And Data
- Dataprocessing
- Creating ML Model
- Creating A Flask App
- Download The Project Files
Project-10: Intel Image Classification Flask App
- Introduction
- Importing and processing data
- Creating a Model
- Creating a Flask App
- Download The Project Files
Project-11: Sentiment Analysis Django App -Deploy On Heroku
- Introduction to Sentiment Analysis
- Project Notebook Google Colab
- Building Django App
- Deploying App in heroku
- Download The Project Files
Project-12: Attrition Rate Django Application
- Introduction
- Creating Colab Notebook
- Creating Django App
- Deploying App in heroku
- Download The Project Files
Project-13: Find Legendary Pokemon Django App -Deploy On Heroku
- Introduction
- Creating Colab Notebook
- Creating DJango App
- Deploying App in heroku
- Download The Project Files
Project-14: Face Detection Streamlit App
- Introduction
- Creating The Face App
- Creating The face app
- Creating The Face app
- Download The Project Files
Project-15: Cats Vs Dogs Classification Flask App
- Introduction
- Creating Project Notebook
- Building Model
- Building Flask App
- App Deployment
- Download The Project Files
Project-16: Customer Revenue Prediction App -Deploy On Heroku
- Introduction
- Colab Notebook
- Creating Flask App
- Deploying Flask App
- Download The Project Files
Project-17: Gender From Voice Prediction App -Deploy On Heroku
- Introduction
- Creating Project Notebook
- Creating Project App Django
- Deploying The App
- Download The Project Files
Project-18: Restaurant Recommendation System
- Introduction
- Creating Colab Notebook
- Exploratory Data Analysis
- Data Analysis2
- Download The Project Files
Project-19: Happiness Ranking Django App -Deploy On Heroku
- Introduction
- Project Notebook
- Creating Django App
- Deploying Django App
- Download The Project Files
Project-20: Forest Fire Prediction Django App -Deploy On Heroku
- Introduction
- Model building part1
- Model building part2
- Model building part3
- Django Application part1
- Django Application part2
- Deploying on Heroku
- Download The Project Files
Project-22: Build Affair Count Django App -Deploy On Heroku
- Introduction
- Machine Learning model building
- Feature Selection
- Model Building
- Django Application
- Django Application building
- Deploying on Heroku
- Download The Project Files
Project-23: Build Shrooming Predictions App -Deploy On Heroku
- Introduction
- Importing libraries
- Building the model
- Building Django Application
- Deploying on Heroku
- Download The Project Files
Project-24: Google Play App Rating prediction With Deployment On Heroku
- Introduction
- Introduction to libraries and dataset
- Preprocessing the data
- building the model
- Django Application
- Deploying to Heroku
- Download The Project Files
Project-25: Build Bank Customers Predictions Django App -Deploy On Heroku
- Introduction
- Importing Libraries and understanding data
- Building and training the model
- Django Application
- Deploying on heroku
- Download The Project Files
Project-26: Build Artist Sculpture Cost Prediction Django App -Deploy On Heroku
- Introduction
- Understanding the data
- Outliers and Model
- Building Django Application
- Deploying to Heroku
- Download The Project Files
Project-27: Build Medical Cost Predictions Django App -Deploy On Heroku
- Introduction
- Introduction and handling the data
- Building the model
- Django Application
- Heroku Deployment
- Download The Project Files
Project-28: Phishing Webpages Classification Django App -Deploy On Heroku
- Introduction
- Understanding the data
- Feature Selection and model building
- Django Application
- Deploying on Heroku
- Download The Project Files
Project-29: Clothing Fit-Size predictions Django App -Deploy On Heroku
- Introduction
- Understanding the data
- Cleaning the data
- Building the model
- Implementing Django Application
- Deploying on heroku
- Download The Project Files
Project-30: Build Similarity In-Text Django App -Deploy On Heroku
- Introduction
- Cleaning the data
- Building the model
- Implementing Django web application
- Deploying on Heroku
- Download The Project Files
Project-31: Heart Attack Risk Prediction Using Eval ML (Auto ML)
- Introduction to the Project
- Importing Libraries and Datasets
- Data Analysis
- Model Building Part 1
- Model Building Part 2
- Model building and Predictions using Auto ML
- Download The Project Files
Project-32: Credit Card Fraud Detection Using Pycaret (Auto ML)
- Introduction to the Project
- Importing Libraries and DataSet
- Data Analysis
- Model Building using ML
- Model Building and Prediction using PyCaret (AutoML)
- Download The Project Files
Project-33: Flight Fare Prediction Using Auto SK Learn (Auto ML)
- Introduction to the Project
- Importing Libraries and DataSet
- Data Analysis
- Feature Engineering 1
- Feature Engineering 2
- Feature Selection
- Model Building using ML
- Model Building and Prediction using Auto SK Learn
- Download The Project Files
Project-34: Petrol Price Forecasting Using Auto Keras
- Introduction to the Project
- Importing Libraries and Data Set
- Data Analysis and splitting of Data
- Data Preprocessing
- Model Building and Prediction using LSTM model
- Model Building and prediction using ARIMA and Auto Keras(Auto ML)
- Download The Project Files
Project-35: Bank Customer Churn Prediction Using H2O Auto ML
- Introduction to the Project
- Importing Libraries and DataSet
- Data Analysis
- Feature Engineering
- Model Building and Prediction using ANN
- Model Building and Prediction using H2O Auto ML(Auto ML)
- Download The Project Files
Project-36: Air Quality Index Predictor Using TPOT With Deployment (Auto ML)
- Introduction to the Project
- Importing Libraries and Dataset
- Data Analysis
- Feature Engineering
- Model Building using ML- 1
- Model Building using ML- 2
- Model Building and Predictions using TPOT Library (Auto ML)
- Deployment of Model using Flask API
- Download The Project Files
Project-37: Rain Prediction Using ML models $ PyCaret With Deployment (Auto ML)
- Introduction to the Project
- Importing Libraries and DataSet
- Data Analysis and Handling Missing Values- 1
- Data Analysis and Handling Missing Values- 2
- Feature Engineering
- Model Building using ML Algorithms
- Model Building and Prediction using PyCaret (AutoML)
- Using FLASK API
- Deploying model using Heroku
- Download The Project Files
Project-38: Pizza Price Prediction Using ML And EVALML(Auto ML)
- Introduction to the project
- Importing Libraries and DataSet
- Data Analysis
- Feature Engineering
- Model Building
- Model Building and Prediction using EVAL ML(Auto ML)
- Download The Project Files
Project-39: IPL Cricket Score Prediction Using TPOT (Auto ML)
- Introduction to the Project
- Importing Libraries and DataSet
- Data Analysis and Cleaning
- Data Preprocessing
- Model Building using ML Algorithms
- Model Building using TPOT Auto ML Library-1
- Model Building using TPOT Auto ML Library-2
- Download The Project Files
Project-40: Predicting Bike Rentals Count Using ML And H2O Auto ML
- Introduction to the Project
- Importing libraries and DataSet
- Data Analysis and Cleaning -1
- Data Analysis and Cleaning -2
- Data Preprocessing
- Splitting the Data
- Model Building and Prediction using ML
- Model Building and Prediction using H2O Auto ML Library
- Download The Project Files
Project-41: Concrete Compressive Strength Prediction Using Auto Keras (Auto ML)
- Introduction to the Project
- Importing Libraries and DataSet
- Data Analysis
- Feature Engineering
- Model Building and Prediction using Deep Learning
- Model Building and Prediction using Auto Keras(Auto ML)
- Download The Project Files
Project-42: Bangalore House Price Prediction Using Auto SK Learn (Auto ML)
- Introduction to the Project
- Importing Libraries and DataSet
- Data Analysis and Feature Engineering
- Data Preprocessing 1
- Data Preprocessing 2
- Model Building and Prediction using ML
- Model Building and Prediction using Auto SK Learn(Auto ML)
- Download The Project Files
Project-43: Hospital Mortality Prediction Using PyCaret (Auto ML)
- Introduction to the Project
- Importing Libraries and DataSet
- Data Analysis and Preprocessing 1
- Data Analysis and Preprocessing 2
- Model Building using ML
- Model Building using Auto ML(PyCaret)
- Download The Project Files
Project-44: Employee Evaluation For Promotion Using ML And Eval Auto ML
- Introduction to the Project
- Importing Libraries and DataSet
- Data Analysis and Preprocessing 1
- Data Analysis and Preprocessing 2
- Model Building uisng ML
- Model Building and Prediction using Eval Auto ML
- Download The Project Files
Project-45: Drinking Water Potability Prediction Using ML And H2O Auto ML
- Introduction to the Project
- Importing Libraries and DataSet
- Data Analysis
- Feature Engineering
- Model Building using ML
- Model Building and Prediction using H2O Auto ML
- Download The Project Files
Project-46: Black Friday Sale Project
- Importing libraries and data
- Understanding data
- Data visualization and data preprocessing
- Model building part1
- Model building part2
- Download The Project Files
Project-47: Sentiment Analysis Project
- Importing libraries and data
- Text normalization
- Lemmatization
- Data preprocessing
- Model Building
- Download The Project Files
Project-48: Parkinson’s Disease Prediction Project
- Importing libraries and data
- Understanding the data
- data visualization
- Model building part 1
- Model building part 2
- Download The Project Files
Project-49: Fake News Classifier Project
- Importing libraries and data
- data preprocessing
- Text cleaning
- Vectorizer
- Model Building
- Download The Project Files
Project-50: Toxic Comment Classifier Project
- Importing libraries and data
- Understanding data
- data visualization and preprocessing
- Balancing the target column
- Model building
- Model evaluation
- Download The Project Files
Project-51: Language Translator App Using IBM Cloud Service -Deploy On Heroku
- Introduction -Language Translator App Using IBM Cloud Service -Deploy On Heroku
- Setting Service
- Integrating Service
- Coding the UI
- Deployment on Heroku
- Download The Project Files
Project-52: Predict Views On Advertisement Using IBM Watson -Deploy On Heroku
- Project Overview
- Introduction
- Setting up Watson Studio Part-1
- Setting up Watson Studio Part-2
- Deploying the Model on Deployment Center
- Integrating Watson Service with UI
- Deployment on Heroku Cloud
- Download The Project Files
Project-53: Laptop Price Predictor -Deploy On Heroku
- Overview -Laptop Price Predictor -Deploy On Heroku
- EDA Part-1
- EDA Part-2
- EDA Part-3
- EDA Part-4
- EDA Part-5
- EDA Part-6
- EDA Part-7
- Model Building Part-1
- Model Building Part-2
- Model Building Part-3
- Model Building Part-4
- Model Building Part-5
- Integrating with UI
- Deployment on Heroku
- Download The Project Files
Project-54: WhatsApp Text Analyzer -Deploy On Heroku
- Introduction - WhatsApp Text Analyzer -Deploy On Heroku
- Fetching Data from Whatsapp
- Project Structure
- Text Processing Part 1
- Text Processing Part2
- Text Processing Part 3
- Text Processing Part 4
- Text Analytics Part 1
- Text Analytics Part 2
- Text Analytics Part 3
- Text Analytics Part 4
- Text Analytics Part 5
- Text Analytics Part 6
- Deployment on Heroku Cloud
- Download The Project Files
Project-55: Course Recommendation System -Deploy On Heroku
- Introduction
- Coding Recommendation System
- Integrating with Flask Server
- Exploratory Data Analysis
- Integrating Python Code with JavaScript
- Deployment on Heroku Cloud
- Download The Project Files
Project-56: IPL Match Win Predictor -Deploy On Heroku
- Introduction
- EDA Part 1
- EDA Part 2
- EDA Part 3
- EDA Part 4
- Model Building
- Coding the UI
- Deployment on Heroku Cloud
- Download The Project Files
Project-57: Body Fat Estimator App -Deploy On Microsoft Azure
- Introduction
- EDA Part 1
- EDA Part 2
- Feature Selection Part 1
- Feature Selection Part 2
- Model Building
- Model Evaluation
- Coding the UI Part 1
- Coding the UI Part 2
- Model Deployment on Azure Part 1
- Model Deployment on Azure Part 2
- Download The Project Files
Project-58: Campus Placement Predictor App -Deploy On Microsoft Azure
- Introduction
- Data Preprocessing
- EDA Part 1
- EDA Part 2
- Feature Selection
- Model Building
- Hyper Parameter Tuning, Model Testing
- Coding the UI Part 1
- Coding the UI Part 2
- Coding the UI Part 3
- Deployment Part 1 -Deploy On Microsoft Azure
- Deployment Part 2
- Download The Project Files
Project-59: Car Acceptability Predictor -Deploy On Google Cloud
- Introduction
- Data Preprocessing
- Model Building
- Coding the UI
- Integrating Jinja Framework
- Integrating JavaScript with Flask
- Deployment on Google Cloud Platform -GCP
- Download The Project Files
Project-60: Book Genre Classification App -Deploy On Amazon Web Services
- Introduction
- Text Processing Part1
- Text Processing Part2
- Model Building
- Model Testing
- Integrating Model with Flask
- Touch points on Amazon Web Services -AWS
- Deploying model on AWS EC2 instance
- Fixing the Errors
- Download The Project Files
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