About Course

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

Course Content

Excel
In this module we will see excel for Data Science

Excel Introduction & Math Formulas

50:25
Text, Datetime, Logical Function

56:28
Lookup & Formatting, Data Validation

44:17
Charts, Macros, Shortcuts

50:34

Python

Environment setup – 1

01:00:42
Basics Data Types 2

01:00:44
Data Type and Data Structure 3

01:00:43
Data Structure & String Formatting 4

58:18
Conditional Statement 5

58:46
Functions & Lambda(Advance Function) 6

01:00:08
Function & Modules 7

01:00:05
Numpy 8

01:00:28
Pandas, Matplotlib, Seaborn, Exception Handling 9

56:50

Machine Learning
In this module, we learn Machine Learning according to Data Science.

Machine Learning Introduction 1

01:00:28
Linear & Logistic Regression 2

59:47
KNN 3

58:54
Decision Tree 4

01:00:28
Random Forest & Extra Random Trees 5

52:54
XGBOOST 6

51:30
DBSCAN Clustering 9

51:05
Neural Network 7

55:56
Ridge and Loasso Regularization 10

50:47
Bank Loan Prediction Project

54:54
K Means Clustering & Mini Batch K Means Clustering 8

50:31

NLP

Introduction to NLP 1

50:56
Tagging & HMM 2

53:56
Naive Bayes & Sentiment Analysis 3

52:42
Word2Vec, Embedding, Dot Product 4

56:38
Neural Network, RNN, Bi-Directional RNN 5

52:36
Practical Implementation of Count Vectorizer(Weather Disaster) 6

52:10
Practical Implementation of Amazon Alexa dataset 7

41:35
POS tagging & NER 8

44:45
News Headline Sarcasm Detection, LDA, Gensim 9

46:42
NLP Weather Prediction Project Part -1

07:00
NLP Weather Prediction Project Part – 2

55:06

Deep Learning

Introduction to Deep Learning 1

51:15
MNIST Handwritten digit classification 2

44:06
CNN 3

43:59
CNN Implementation 4

51:37
RCNN, Fast RCNN, Faster RCNN, Tensorflow HUB 5

46:43
Fast RCNN Implementation 6

32:16
Model Deployment 7

23:00
YOLO V4 Project 8

50:45
Detectron2 Model 9

39:45
Sentiment Classification with Neural Network

01:01:08

About Course

CURRICULUM

Excel

Python

Machine Learning

Projects

NLP

Project

Deep Learning

Project

Our Certifications

What Will You Learn?

Course Content

Excel In this module we will see excel for Data Science

Excel Introduction & Math Formulas

Text, Datetime, Logical Function

Lookup & Formatting, Data Validation

Charts, Macros, Shortcuts

Python

Environment setup – 1

Basics Data Types 2

Data Type and Data Structure 3

Data Structure & String Formatting 4

Conditional Statement 5

Functions & Lambda(Advance Function) 6

Function & Modules 7

Numpy 8

Pandas, Matplotlib, Seaborn, Exception Handling 9

Machine Learning In this module, we learn Machine Learning according to Data Science.

Machine Learning Introduction 1

Linear & Logistic Regression 2

KNN 3

Decision Tree 4

Random Forest & Extra Random Trees 5

XGBOOST 6

DBSCAN Clustering 9

Neural Network 7

Ridge and Loasso Regularization 10

Bank Loan Prediction Project

K Means Clustering & Mini Batch K Means Clustering 8

NLP

Introduction to NLP 1

Tagging & HMM 2

Naive Bayes & Sentiment Analysis 3

Word2Vec, Embedding, Dot Product 4

Neural Network, RNN, Bi-Directional RNN 5

Practical Implementation of Count Vectorizer(Weather Disaster) 6

Practical Implementation of Amazon Alexa dataset 7

POS tagging & NER 8

News Headline Sarcasm Detection, LDA, Gensim 9

NLP Weather Prediction Project Part -1

NLP Weather Prediction Project Part – 2

Deep Learning

Introduction to Deep Learning 1

MNIST Handwritten digit classification 2

CNN 3

CNN Implementation 4

RCNN, Fast RCNN, Faster RCNN, Tensorflow HUB 5

Fast RCNN Implementation 6

Model Deployment 7

YOLO V4 Project 8

Detectron2 Model 9

Sentiment Classification with Neural Network

Excel
In this module we will see excel for Data Science

Machine Learning
In this module, we learn Machine Learning according to Data Science.