Docker Vulnerability remediation:• Updated the Docker files with necessary changes to run Docker container as non-rootuser, replaced the base image with golden image and attached required labels for the Docker image.• Build the Docker images locally, modified the Linux commands in Docker file as stated by the requirements and pushed it to Git repo.Automating and Building ETL Pipelines:• Build the ETL pipelines to o Extracted data from 3 different API Endpoints which give the json result, o Transformed these json results into tabular formato And Loaded this transformed data into snowflake tables• Data modelled these snowflake tables in Star Schema.• Using Apace airflow, deployed this ETL pipeline in dagger environment, which reduced manual redundancy of 90%Automate Sending Emails:• Build an ETL pipeline to call the different API’s and load it into snowflake Tables• Developed the Python Script to send an Email to the required PDS, about their dataset issues.• deployed this ETL pipeline in dagger environment, which reduced manual redundancy of 100%Tableau Dashboards:• Build the tableau Dashboard by connecting to snowflake tables, which helped our in-house customer to get detailed view of their datasets and details. • Created a view of the datasets and their migration statuses, pre migration errors with respective to each LOB and PDS. Migration helper Tools:• FS-ART: Build the python utility using selenium framework to help our customers for automating the dataset registration/migration process.• Validation utility: Build the python utility which helped out customers to validate their datasets in new platform and old platform• Researched and documented the steps to migrate the pipelines from legacy to new infrastructure• Initiated the Inventory collection for OneStream migration, which Kick started the migration process.• Organized and addressed customer’s questions on slack and office hours.

# 600+ hours of hands-on course material, with 1:1 industry expert mentor oversight, and completion of 2 in-depth portfolio projects# Mastered skills in Programming in Python, Software engineering, Data wrangling, Inferential statistics, Machine learning, Deep learning, Data at scale, Data storytelling, Model deployment, Recommendation systems, Time-series analysis, Social Network Analysis# Capstone 1: Microsoft malware Prediction- Loaded the csv file using Dask data frame, to save time and space- explored the factors impacting the machine to be affected by malware.- Implemented Random Forest, LightGBM, XGBoost classifiers to predict whether a Windows machine’s probability of getting infected by malware.# Capstone 2: The story of Film & Recommender systems- Scraped data from the official TMDB Website to create a jumbo Movies Dataset. - Garnered more than 1500 downloads.- Narrated the history of cinema using data on movies from 1874 to 2019.- Implemented various content based and collaborative filter based recommendation engines to come up with a Hybrid Recommender.# Mini projects included, three exploratory data analysis (EDA) projects, linear and logistic regression, recommendation system, Naïve Bays, customer segmentation using clustering, map reduce with Spark