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Hi there, I'm Ashlesh Khajbage!

Welcome to my profile😊 , I hope the studies I present will be helpful to you💪 .

Master's in Data Science graduate with expertise in data engineering, analysis, and science, seeking full-time roles.

With 3 years of professional experience in both Data Engineering and Analysis, I am eager to transition into a full-stack Data Engineer role within the Finance Services, Media and Entertainment, or Health and Life Sciences industries. My passion lies in leveraging ETL tools to solve data-driven problems and make a tangible impact. Alongside my expertise in statistics, machine learning, deep learning, natural language processing, and big data techniques, I am particularly drawn to opportunities in Data Engineering, Data Analysis, or Data Science roles.

Data Engineer Proficiency

  • ETL (Extract, Transform, Load) Tools: Apache Spark, Apache Airflow, Talend, Informatica PowerCenter, and Microsoft SSIS (SQL Server Integration Services).
  • Big Data Platforms: Apache Hadoop, HDFS, Hive, HBase, Apache Kafka
  • Data Warehousing Solutions: Microsoft Azure SQL Data Warehouse, Google BigQuery, Snowflake.
  • Database Management Systems (DBMS): PostgreSQL, MySQL, Oracle, Microsoft SQL Server, and MongoDB.
  • Cloud Platforms: Microsoft Azure, Google Cloud Platform (GCP), and AWS.
  • Data Integration and Visualization Tools: Tableau, Microsoft PowerBI, QlikView, and Looker.
  • Version Control Systems: Git.
  • Programming Languages: Python, Java, Scala, and SQL.

Certifications

  • Microsoft : Azure Data Engineer Associate - link
  • DataBricks : Generative AI Fundamentals - link
  • DataCamp : Associate Data Analyst link
  • DataCamp : Associate Data Scientist - link
  • Google : Google Data Analytics - link
  • IBM : IBM Data Science - link
  • DeepLearning.ai : Deep Learning & Practical Data Science Specialization - link 1 -link 2

[:purple_heart:] I hold a Data Science degree from the Illinois Institute of Technology, where I completed a rigorous curriculum covering Applied Statistics, Probabilities and Statistics, Machine Learning, Big Data technologies, Data Preparation and Analysis, Data Science Practicum, Deep Learning, Natural Language Processing, Project Management, Introduction to Algorithms, and Monte Carlo Methods in Finance.

[:mailbox:] I always believe that i will learn something new from others, that's why I appreciate connection! You can connect me on Linkedin or feel free to throw me a letter via [email protected].

githubbadge Gmail Badge Facebook Kaggle Badge ashleshK

Find me on:

LeetCode: leetcode.com/Astro_boy/
Geeksforgeeks: geeksforgeeks.com/ashleshkhajbage
HackerRank: hackerrank.com/ashleshuk

Connect with me:


Ashlesh Khajbage's Projects

labview-basics-to-master icon labview-basics-to-master

This repository contains project done in LabView IDE from Basic Gates designing, Adders, Counters, Encoders, Decoders and Examples to connect to external Arduino like embedded systems

lane-detection icon lane-detection

Lane line detection is a crucial feature of Self-Driving Vehicles

leetcode-programming-codes icon leetcode-programming-codes

This Repository consists of Programming codes for various Learning Tracks varying from 30 days of coding to specific data structure coding problems.

machine-learning-data-science-deep-learning icon machine-learning-data-science-deep-learning

This Repository Consists All Courses, Projects and Online Learning Done in Context of Machine learning, Data Sceince And Deep Learning From Various Sources like Youtube, Coursera, Udemy And WEbsites like Scikit, Keras

machine-learning-stanford-andrew-ng icon machine-learning-stanford-andrew-ng

# Machine Learning (Coursera) This is my solution to all the programming assignments and quizzes of Machine-Learning (Coursera) taught by Andrew Ng. After completing this course you will get a broad idea of Machine learning algorithms. Try to solve all the assignments by yourself first, but if you get stuck somewhere then feel free to browse the code. ## Contents * Lectures Slides * Solution to programming assignment * Solution to Quizzes by Andrew Ng, Stanford University, [Coursera](https://www.coursera.org/learn/machine-learning/home/welcome) ### Week 1 - [X] Videos: Introduction - [X] Quiz: Introduction - [X] Videos: Linear Regression with One Variable - [X] Quiz: Linear Regression with One Variable ### Week 2 - [X] Videos: Linear Regression with Multiple Variables - [X] Quiz: Linear Regression with Multiple Variables - [X] Videos: Octave/Matlab Tutorial - [X] Quiz: Octave/Matlab Tutorial - [X] Programming Assignment: Linear Regression ### Week 3 - [X] Videos: Logistic Regression - [X] Quiz: Logistic Regression - [X] Videos: Regularization - [X] Quiz: Regularization - [X] Programming Assignment: Logistic Regression ### Week 4 - [X] Videos: Neural Networks: Representation - [X] Quiz: Neural Networks: Representation - [X] Programming Assignment: Multi-class Classification and Neural Networks ### Week 5 - [X] Videos: Neural Networks: Learning - [X] Quiz: Neural Networks: Learning - [X] Programming Assignment: Neural Network Learning ### Week 6 - [X] Videos: Advice for Applying Machine Learning - [X] Quiz: Advice for Applying Machine Learning - [X] Videos: Programming Assignment: Regularized Linear Regression and Bias/Variance - [X] Machine Learning System Design - [X] Quiz: Machine Learning System Design ### Week 7 - [X] Videos: Support Vector Machines - [X] Quiz: Support Vector Machines - [X] Programming Assignment: Support Vector Machines ### Week 8 - [X] Videos: Unsupervised Learning - [X] Quiz: Unsupervised Learning - [X] Videos: Dimensionality Reduction - [X] Quiz: Principal Component Analysis - [X] Programming Assignment: K-Means Clustering and PCA ### Week 9 - [X] Videos: Anomaly Detection - [X] Quiz: Anomaly Detection - [X] Videos: Recommender Systems - [X] Quiz: Recommender Systems - [X] Programming Assignment: Anomaly Detection and Recommender Systems ### Week 10 - [X] Videos: Large Scale Machine Learning - [X] Quiz: Large Scale Machine Learning ### Week 11 - [X] Videos: Application Example: Photo OCR - [X] Quiz: Application: Photo OCR ## Certificate * [Verified Certificate]() ## References [[1] Machine Learning - Stanford University](https://www.coursera.org/learn/machine-learning)

mini-projects icon mini-projects

Implemented Content-Based Movie Recommeder System, Covid-19 Recognition using AI, Automated Tweet Generator, Fake Job Detection, US Consumer Finance Complaint Classification

multisim-simulation icon multisim-simulation

Contains basic Simulation circuit layout for concepts involved in Electronic Devices and Circuits and Integrated Circuits Subjects

my-store icon my-store

First Full Fledged My Store demo Web App

node-notes icon node-notes

Node-Note is an node.js app that enables user to Add, Read, List and Remove note from notes-data.js file

node-tests icon node-tests

this app contains the tools and library used for testing your app and server. library like supertest and expect were used

online-test icon online-test

An simple Test based on swing without using Database

power-bi-a-z-hands-on-power-bi-training-for-data-science-udemy icon power-bi-a-z-hands-on-power-bi-training-for-data-science-udemy

Learn data visualization through Microsoft Power BI and create opportunities for you or key decision makers to discover data patterns such as customer purchase behavior, sales trends, or production bottlenecks. You'll learn all of the features in Power BI that allow you to explore, experiment with, fix, prepare, and present data easily, quickly, and beautifully.

practical-data-science-on-the-aws-cloud-specialization icon practical-data-science-on-the-aws-cloud-specialization

@DeepLearning.AI Practical Data Science Specialization brings together these disciplines using purpose-built ML tools in the AWS cloud. It has helped me to develop the practical skills to effectively deploy your data science projects and overcome challenges at each step of the ML workflow using Amazon SageMaker.

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