WELCOME



Become a

Full-Stack Data Scientist

In 9 Months



Average Salary

of A Full Stack Data Scientist:

$125,000



Join The 6-Figure Career

What You Get In This Course:

Python Programming For Data Science
Python Programming For Data Science

Master Python for data science. Gain a solid background in Python program. Learn robust Python libraries and frameworks such as Numpy, Pandas, Matpltlib, Seaborn, Plotly, ggplot, SKlearn, etc.

Statistics For Data Science

Master the essentials of Statistics that you need to become an efficient and productive Data Scientist.

Machine Learning

Learn robust and modern Machine Learning concepts such as Regression Analysis, Naive Bayes & K- Nearest Neighbor(KNN), SVM, Principal Component Analysis(PCA), Random Forests, Bagging, Boosting, etc.



Web Scraping For Data Science

Learn how data scientist perform professional web scraping to fetch data from various web portals to solve business problems. Learn robust data science web scraping tools and techniques and frameworks like Beautifulsoup, Request, Selenium, and Scrapy.

Recommendation Systems

Build your own movie recommendation system with User interface like Netflix and perform recommendations in real time.

Gain a hands-on understanding of how platforms like Netflix, Amazon, Youtube, Facebook, etc recommend products to customers.

Learn the various recommendation techniques available and how to build your own recommendation systems.

Cloud Deployment

Learn how to build and deploy your own machine learning models and build ML apps for your model. Learn cloud to deploy to cloud platforms such as Amazon Web Service(AWS), Google Cloud(GCP), Microsoft Azure, Heroku, Flask, Streamlit, etc.

Artificial Intelligence (AI)

Artificial intelligence is by far the most robust human inventions of all time. Thing about how netflix is implementing AI into their recommendation systems or how facebook is matching you with several friends, it's all about AI.

Learn the latest AI techniques to create robust apps and projects.

Deep Learning

Be equipped with the industry deep learning techniques needed for performing computer vision and natural language processing(NLP) task

Computer Vision

Eager to know how iPhones recognizes your face? How machine learning models are able to identify cancer and tumors in cells, or how Tesla is using computer vision to build self driving cars? this is the section you will learn all that.

Learn how to build your own computer vision systems that can recognize objects accurately.

Natural Language Processing (NLP)

Learn how we use Natural Language Processing to processing text at the banking sector as well as other sectors. Build your own NLP model that can process text at a faster rate and efficiently.

Hands-On Projects


Gain a practical understanding of the concepts by working on 15+ carefully selected Projects and Assignments.

2 SPECIALIZATIONS


Specializing In Two Areas


Computer Vision (CV)

Natural Language Process (NLP)


Course Curriculum Walkthrough



You can DOWNLOAD Course Curriculum






See Course Curriculum

A Well-Structured 9-Month Course Curriculum



Over 125 hours of Up-to-date Quality Course Content.


  DATA SCIENCE & MACHINE LEARNING WARM-UP
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  CURRICULUM
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  1ST MONTH
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  WEEK 1 :: Data Science Overview
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  COMPLETE SQL FOR DATA SCIENCE COURSE
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  SQL : BEGINNER LEVEL
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  SQL Commands
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  Understanding and Creating SQL Databases
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  Understanding and Creating SQL Tables
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  Types Of SQL KEYS
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  Data Types In SQL
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  CREATE Table and INSERT Data into Table
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  SQL Constraints
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  WEEK 2 :: SQL INTERMEDIATE LEVEL
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  SQL JOINS
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  Working With Existing SQL Table
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  SQL VIEW
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  SQL Data Summarization: Aggregation Functions
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  Advance SQL Functions
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  WEEK 3 :: SQL ADVANCED LEVEL
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  SQL Stored Procedure
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  Triggers
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  RECOMMENDATION
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  WEEK 4 :: BEGINNER : Python For Data Science
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  Datasets
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  Hands-On With Python
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  Python Output(), Input() and Import() Functions
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  Python Operators
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  Python Flow Control
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  WEEK 2: Python Functions
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  Python Global and Local Variables
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  Working With Files In Python
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  Python Modules
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  Python Packages and Libraries
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  Data Types In Python
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  Extra Content
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  WEEK 3: Numpy
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  Numpy Assignment
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  WEEK 4: Pandas
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  Data Visualisation: MatplotIib And Seaborn
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  PROJECT: Python Assignment
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  PYTHON PROJECTS
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  2ND MONTH
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  FULL STATISTICS FOR DATA SCIENCE
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  Statistical Methods Deep Dive
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  Data
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  Recommend Statistics For Data Science
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  Frequency Distribution
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  Central Tendency
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  Measures of Dispersion
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  Coefficient of Variations
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  The Five Number Summary & The Quartiles
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  The Normal Distribution
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  Correlation
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  3RD MONTH
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  WEEK 1 :: Probability
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  Baye's Theorem
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  Hypothesis Testing
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  STATISTICS PROJECT
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  GITHUB For Data Science
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  ARTIFICIAL INTELLIGENCE(AI) and MACHINE LEARNING(ML)
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  WEEK 2 :: FULL MACHINE LEARNING COURSE
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  USE CASE
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  Machine Learning Algorithms
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  Working with Machine Learning Data
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  WEEK 3 :: SUPERVISED MACHINE LEARNING ALGORITHMS
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  Regression
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  Linear Regression
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  LAB SESSION: Linear Regression
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  Logistic Regression Algorithm
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  Naive Bayes Algorithm
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  K-Nearest Neigbhor Algorithm (KNN)
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  Support Vector Machine (SVM) Algorithm
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  Machine Learning Algorithm Performance Metrics
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  Decision Tree Algorithm
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  WEEK 4 :: Ensemble Techniques
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  Overfitting and Underfitting
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  Bias vs Variance
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  PROJECT: Supervised Machine Learning
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  4TH MONTH
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  UNSUPERVISED MACHINE LEARNING ALGORITHMS
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  WEEK 3: K-Means Clustering Algorithm
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  Hierarchical Clustering Algorithm
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  Principal Component Analysis (PCA)
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  PROJECT: Unsupervised Machine Learning
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  Feature Engineering : Model Selection & Optimization
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  WEEK 3 :: WEB SCRAPING
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  PROJECT: Wikipedia Web Scraping
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  PROJECT: Online Book Store Web Scrapping
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  Web Scraping: Building Amazon Auto Scraper
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  PROJECT: Job Board Data Web Scraping Automation With Python
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  Automate Spotify & Youtube with Python
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  WEEK 4 :: RECOMMENDATION SYSTEMS
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  4TH MONTH
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  HANDS-ON PROJECTS
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  Bank Note Analysis
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  Big Mart Sales Prediction
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  Amazon.com Employee Access Challenge
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  Breast Cancer Detection using SVM and KNN : PART 1
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  Predicting Compressive Strength Of Concrete
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  Stock Market Clustering
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  5TH MONTH
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  CLOUD DEPLOYMENT
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  Streamlit For Building Machine Learning Apps
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  FLASK TUTORIAL
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  WEEK 1 ::End-to-End Machine Learning with DEPLOYMENT : Predict Restaurant Rating
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  CLOUD :: Heroku Machine Learning Cloud Deployment
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  CLOUD :: Amazon Web Service (AWS) Deployment
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  CLOUD :: Microsoft Azure Deployment
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  WEEK 2 :: PROJECTS SESSION: MACHINE LEARNING
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  ML PROJECTS: Building a Netflix Recommendation System
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  5TH MONTH
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  ML PROJECTS: Building CRUD App
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  ML PROJECT: Building Covid-19 Report Dashboard for Berlin City
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  ML PROJECTS: Building IPL Score Predictor App
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  ML PROJECTS: Building a Sales Forcast App
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  ML PROJECTS: Building A Breast Cancer Predictor App : PART 2
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  WEEK 4 :: SCIENTIFIC RESEARCH PAPER
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  6TH MONTH
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  ARTIFICIAL INTELLIGENCE
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  WEEK 1 :: DEEP LEARNING
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  Artificial Neural Network
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  WEEK 2 :: Activation Functions
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  Tensorflow and Keras
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  LAB SESSION: Deep Learning(ANN)
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  WEEK 3 :: FULL COMPUTER VISION COURSE
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  COMPUTER VISION (CV): Beginner Level
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  CPU vs GPU vs TPU
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  COMPUTER VISION: Intermediate Level
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  WEEK 4 :: COMPUTER VISION: Advanced Level
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  CNN Architectures
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  Transfer Learning
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  Object Detection
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  Performance Metrics for Object Detection
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  Objection Detection Techniques
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  7TH MONTH
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  WEEK 1 :: OPENCV FULL TUTORIAL
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  PROJECTS: COMPUTER VISION PROJECTS
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  CV PROJECT: Car Parking Space Counter Using OpenCV
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  CV PROJECT(Kaggle): Fruit and Vegetable Classification
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  CV PROJECT: Predicting Lung Disease with Computer Vision
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  WEEK 2 :: CV PROJECT: Nose Mask Detection with Computer Vision
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  CV PROJECT: Pose Detection
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  CV PROJECT: Building a virtual AI Keyboard
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  CV PROJECT: Yolov4 Object Detection Using Webcam
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  WEEK 3 :: NATURAL LANGUAGE PROCESSING(NLP)
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  Hands-On NLP: Text Pre-processing
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  Text Pre-processing: Normalization
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  WEEK 4 :: Part Of Speech (POS) Tagging
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  Hands-On Text Pre-processing
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  Introduction To Statistical NLP Techniques
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  Language Modeling
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  8TH MONTH
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  WEEK 1 :: INTERMEDIATE LEVEL: Word Embeddings
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  Word2Vec
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  GloVe
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  Sentence Parsing
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  Sequential Models
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  WEEK 2 :: ADVANCED LEVEL: Recurrent Neural Network (RNN)
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  LSTM
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  Sequence To Sequence Models (Seq2Seq)
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  WEEK 3 :: NLP PROJECT: Sentiment Analyzer
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  Name Entity Recognition (NER)
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  NLP PROJECT: Building a Name Entity Recognition App
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  NLP PROJECT: AI Resume Analyzer App
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  WEEK 4 :: Microsoft Power BI
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