Data Science

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  • Certificate of completion
  • Downloadable resources
 1499

Material Includes

  • 45 Chapters
  • 5 Modules
  • Project with every module
  • Tutorial

Requirements

  • No prior experience is required. We will start from the very basics
  • You’ll need to install Anaconda. We will show you how to do that step by step
  • Microsoft Excel 2003, 2010, 2013, 2016, or 365

Target Audience

  • Anyone who wants to start a career in data science

CURRICULUM

Module 1

Excel

Excel Introduction & Math Formulas
Text, Datetime, Logical Function
Lookup & Formatting, Data Validation
Charts, Macros, Shortcuts

Module 2

Python

Environment setup
Basics Data Types
Data Type and Data Structure
Data Structure & String Formatting
Conditional Statement
Functions & Lambda(Advance Function)
Function & Modules
Numpy
Pandas, Matplotlib, Seaborn, Exception Handling

Module 3

Machine Learning

Machine Learning Introduction
Linear & Logistic Regression
KNN
Decision Tree
Random Forest & Extra Random Trees
XGBOOST
DBSCAN Clustering
Neural Network
Ridge and Loasso Regularization
K Means Clustering & Mini Batch K Means Clustering

Projects

Bank Loan Prediction Project

Module 4

NLP

Introduction to NLP 1
Tagging & HMM
Naive Bayes & Sentiment Analysis
Word2Vec, Embedding, Dot Product
Neural Network, RNN, Bi-Directional RNN
Practical Implementation of Count Vectorizer(Weather Disaster)
Practical Implementation of Amazon Alexa dataset
POS tagging & NER
News Headline Sarcasm Detection, LDA, Gensim

Project

NLP Weather Prediction

Module 5

Deep Learning

Introduction to Deep Learning
MNIST Handwritten digit classification
CNN
CNN Implementation
RCNN, Fast RCNN, Faster RCNN, Tensorflow HUB
Fast RCNN Implementation
Model Deployment
Detectron2 Model
Sentiment Classification with Neural Network

Project

YOLO V4 Project

Our Certifications

Sample Project Completion Certificate
Sample Course Completion Certificate
Sample Project Based Internship Completion Certificate