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Batch Date: Nov 26th @8:30AM

Faculty: Mrs. Sasmitha (10+ Yrs of Exp,..)

Duration: 75 Days

Venue :
DURGA SOFTWARE SOLUTIONS,
Flat No : 202, 2nd Floor,
HUDA Maitrivanam,
Ameerpet, Hyderabad - 500038

Ph.No: +91 - 9246212143, 80 96 96 96 96

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