Suitable for those who want to gain basic to expert level knowledge in Java Programming and build solid Java programming skills for anyone wanting to learn the language. The course will be interactive and will cover core java, Object-Oriented Programming, Exception Handling, File Handling, Testing Junit Mockito, etc.
Includes one capstone project.
I am a software engineer with 2 years of professional experience, currently pursuing a master's at UCD in Computer Science. I have previous experience in teaching data engineering and Java development to students as well as junior engineers. I am skilled in Java, Python, and various big data technologies.
Technical Skills
• Programming Languages: Java, Python, C++
• Databases: MySQL, Neo4j, MongoDB, PostgreSQL
• Deployment and Cloud: Databricks, Google Cloud Platform (GCP), AWS • Big data and Machine Learning: Hadoop, Mapreduce, Apache Spark, Apache Flink, Hive, Kafka, HDFS ,Numpy, Pandas, Scikit Learn, ONNX
• Technologies and tools: Git, Jira, Pytest, Junit, Mockito, Jupyter, Maven, KNIME, Android Development, Kanban
Education
• MSc in Computer Science (Negotiated Learning)
University College Dublin
Dublin, Ireland
◦ Key Modules: Big Data Programming, Data Mining, Cloud Computing, Machine Learning, Data Visualization
• Bachelors of Engineering in Computer Science | GPA: 7.79/10 Aug 2014 – July 2018
Sinhgad Academy of Engineering Pune, India
◦ Key Modules: Data Structures and Algorithms, Operating Systems, Object Oriented Programming
Experience
• Data Engineer - Great Software Laboratory | Pune, India Nov 2018 - Sept 2020
Key Technologies: Java, Python, Spark, Databricks, KNIME, Neo4j
Responsible for writing analytics/validation jobs in Databricks notebooks and KNIME analytics platform to improve data consistency, atomicity, uniqueness, and ML-availability.
Developed Combine Scoring Algorithms (CSA) in Python for different health condition models including COVID which enables employer to perform health check screening of their employees and allow them into office building.
Responsible for creating clinical trial datasets and providing them to data science team.
Developed a POC for offline scoring (edge inference) on android using machine learning, speech processing algorithm and android studio, which decreased overall inference time by ~60%.
Worked on development of an innovative MLOps solution, which closes the gap between modelling and engineering.
Developed a utility for distributed training of machine learning model (estimators) using Spark to speed up model training time. Developed Java procedures on top of Neo4j and setting up a high availability cluster of Neo4j on AWS.
Academic Projects
• Early Detection of Pomegranate Diseases Using Machine Learning and IoT: Machine Learning, Arduino, Java (Aug 2017 – Apr 2018) ◦ The project is developed as a monitoring system consisting of sensors which will identify the chances of crop diseases in its early stages by using Hidden Markov Model and provide alerts to the farmer and the expert.
• Self-driven Car Rental System: Java, MySQL (Jan 2017 – Apr 2017)
Personal Projects
• Data Analytics using New York Taxi data set with Mapreduce and Apache Spark (Feb 2019): Derived insightful information from taxi dataset using MapReduce and Apache Spark and compared performance metrics.
• Streaming Data Analytics with Apache Flink and Kafka (Apr 2019): Wrote streaming Flink program in Java to implement Extract, Transform and Load (ETL) on taxi dataset. Generated a stream of data using Kafka and consumed it with help of flinkkafkaconsumer.
• Football Championship Planner (Jan 2019): Football Championship in Java is a simple project for the management of the football league. It contains a Java code that sets up a tournament of matches executing concurrently using multithreading such that after each round, winning teams advances to the next round until we get the winner.
◦
• Bank Management System (Dec 2018): A bank management system using Java and MySQL with Data Access Object (DAO) Classes and also used Java Design Patterns like Singleton Pattern and Factory Pattern. Test cases are written using Junit Framework.
Conferences & Publications
• IEEE Conference Pune Apr 2018
Technical Speaker | Sensor Networks, Machine Learning
◦Delivered a talk on: Early Detection of Pomegranate Diseases Using Machine Learning and IoT. ◦Published Research Paper in IEEE: The research paper proposes a sensor network consisting of temperature and humidity sensors used for monitoring pomegranate crops and Hidden Markov Model for prediction of diseases like Bacterial Blight, Anthracnose, etc occurring on pomegranate plant. See publication
Extracurricular Coursework
• Unified Data Analytics and ETL (offered by Databricks)
• Data Science on Google Cloud (offered by Google and Qwiklabs)
• Introduction to Big Data with KNIME Analytics Platform (offered by KNIME)
Certifications
• Neo4j Certified Professional Nov 2019
• Certified Core Java Programmer Sept 2016
References available upon request.
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