Course Content

Syllabus:

Artificial Intelligence, MLOPS,

AWS Industry Ready Program

PYTHON Programming

Python Basics

Variable, print(), Taking input from User

Data Types (List , Tuple , Set , Dictionary , String)

Control Statement and Loops (lf Else, While, For)

Functions, Special functions lambda,map, filter, recursion

Python Practice Set-1 (15 Questions)

Python Advance

File handling(Opening,reading,writing,editing,with statements)

Exception Handling(Try,Except,Finally,Raising Exceptions,Asertion)

Object Oriented Programming(Class,Object, Method,Module,Packages)

Inheritance

Python Practice Set-2 (15 Questions)

Python For DataScience- Pandas

Data Frame Basics ,Read-write

Grouping, Merging , Joining and Concatenating Data

sorting, Handling Missing Values

Python Practice Set-3 (15 Questions)

Python For DataScience- Numpy

Creating Arrays

Array methods

Basic Math operations on Arrays

Python Practice Set-4 (15 Questions)

Python For DataScience- Plotly

Scatter Plot, Histogram, Line Plot, Area Plot, Box Plot

Bubble Chart, Bar Plot , Sunburst Chart

Tree Map, Heat Map, Customizing Plots

Python Practice Set-5 (15 Questions)

TABLEAU

Project-1 (Company Sales Dashboard)

Installation, Download Drivers and Connect, Start Page, Navigation

Connect to data Source, Import Excel File, Join Data Bases, Join Files

Creating, Adding, Renaming, Duplicating Worksheet

Calculations, sort and filter data, Different Charts,

Create Dashboards, Filters, Create Stories

Project-1 (Company Sales Dashboard)

MACHINE LEARNING

STATISTICS

Central limit theorem, Correlation

R, R Square, Adj R Square

Variance, Standard Deviation, Quartiles, Inter Quartile Range

Z Score, Normal Distribution

Probability Practice Set (15 Questions)

DATA CLEANING

Data Normalization, Data Standardization, Missing Value Treatment

Multi Collinearity

Outliers Detection and Removal

Feature Selection Techniques,Handling Class imbalance Problems

Project-2 Machine Failure Prediction

REGRESSION

Linear Regression - Know the Math behind

Right Fit, Underfit, Over fit

Validation Technique (RMSE, MSE, MAE)

Project-3 Admission Probability Prediction

CLUSTERING

KMeans - Know the Math behind

Project-5 Document Clustering

DEEP LEARNING

NEURAL NETWORK (ANN)

Perceptron, Activation Functions

Artificial Neural Network Architecture

ANN Learning- Know the Math Behind

Project-6 Stock market Prediction

NLP

TEXT MINING

Web Scraping using beutifulsoup, Selenium

Text Data Preprocessing, Stemming, Lemmatization

Word embedding techniques- count vectorizer, tf-idf vectorizer

Regular expression

Project-7 Web Scraping

MLOPS

MI-FLOW, DOCKER, GITHUB

Model registry, Model Tracking

Concept drift, Data drift

Version control, Containerization

CLOUD COMPUTING

AWS

Storage Services - S3

Compute Services

AWS sage maker, Deployment on AWS

PORTFOLIO BUILDING

Project-8 -->

End to End Deployment (collecting data from Database Cleaning Data ,Visualizing Data, Building Model, Validating and Deploying Models on AWS