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Home
Courses
Data Scientist
Data Science Certification Course
Data Science Training: Best Data Scientist Courses And Certification
Data Science Training: Best Data Scientist Courses And Certification
INTRODUCTION
Introduction Video
DATA SCIENCE FOUNDATION
Introduction to Data Science
Data Science vs Business Analytics vs Big Data
Classification of Business Analytics
Data Science Project Workflow
Various Roles in Data Science
PYTHON FOR DATA SCIENCE
Introduction to Data Science with Python
Python Basics: Basic Syntax, Data Structures
Data objects, Math, Comparison Operators, Condition Statements, loops, lists, tuples, dicts, functions
Numpy Package
Pandas Package
Python Advanced: Data Mugging with Pandas
Python Advanced: Visualization with Matplotlib
Exploratory Data Analysis: Data Cleaning, Data Wrangling
Exploratory Data Analysis: Case Study
STATISTICS FOR DATA SCIENCE
Introduction to Statistics
Harnessing Data
Exploratory Analysis
Distributions
Hypothesis & Computational Techniques
Correlation & Regression
R FOR DATA SCIENCE
Introduction to R Programming
RDBMS (Relational Database Management) Basics
Data Structures – Data Manipulation, Data Visualization using Graphics – GGplot2
Regression Analysis
Classification, Clustering
Association Principles
Building Web Application using Rshinny
VISUAL ANALYTICS FOUNDATION
Visual Analytics Basics
Basic Charts, Plots
SQL FOR DATASCIENCE
Install SQL packages and Connecting to DB
RDBMS (Relational Database Management) Basics
Basics of SQL DB, Primary key, Foreign Key
SELECT SQL command, WHERE Condition
Retrieving Data with SELECT SQL command and WHERE Condition to Pandas Dataframe.
SQL JOINs
Left Join, Right Joins, Multiple Joins
MACHINE LEARNING ASSOCIATE
Machine Learning Introduction
What is ML? ML vs AI. ML Workflow, Statistical Modelling of ML. Application of ML
Machine Learning Algorithms
Popular ML algorithms, Clustering, Classification and Regression, Supervised vs Unsupervised.
Choice of ML
Supervised Learning
Simple and Multiple Linear Regression, KNN, and more
Linear Regression and Logistic Regression
Theory of Linear regression, hands on with use cases
K-Nearest Neighbour (KNN)
Decision Tree
Naïve Bayes Classifier
Unsupervised Learning: K-Means Clustering
MACHINE LEARNING EXPERT
Advanced Machine Learning Concepts
Tuning with Hyper parameters
Random Forest – Ensemble
Ensemble Theory, Random Forest Tuning
Support Vector Machine (SVM)
Simple and Multiple Linear Regression, KNN
Natural Language Processing (NLP)
Text Processing with Vectorization, Sentiment Analysis with Text Blob, Twitter Sentiment Analysis
Naïve Bayes Classifier
Naïve Bayes for Text Classification, New Articles Tagging
Artificial Neural Network (ANN)
Basic ANN network for Regression and Classification
TensorFlow Overview
Deep Learning Intro
NLP ENGINEER
Word2Vector
Named Entity Recognition(NER)
Coreference Resolution
Semantic Network
Topic Modelling, TF-IDF, POS Tagging
Regex for NLP, Text Similarity
Context Understanding Using Bert
Handling Audio Data, Text to Audio, Audio to Text
TIME SERIES FOUNDATION
What is a Time-Series?
Trend, Seasonality, Cyclical and Random
Auto Regressive Model (AR)
Moving Average Model (MA)
ARMA Model
Stationarity of Time Series
ARIMA Model – PredictionConcepts
ARIMA Model Hands on with Python
MODEL DEPLOYEMENT
Basics of Application Program Interface (API)
API basics, loosely Coupled Architecture
Installing Flask
Installation and configuring Flask and cross domain authentication.
End to End ML project with API Deployment
Complete Project Flow with API Deployment and assessing through the website
DEEP LEARNING ENGINEER
Introduction to Deep learning
What is Deep Learning?
Various Deep Learning models in practice and applications
Convolutional Neural Network CNN Intro
Deep Dive into Optimizers, Activation Functions, Loss Functions, Back-Propagation
RNN, LSTM, BERT, Attention based Neural Networks,
Encoder & Decoder, Bi-Directional RNNs
Transfer Learning, Different types of CNN Architectures
Computer Vision Techniques – YOLO, FaceNet
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