Lucy Avetisyan’s Post

Hi All!!!!!!!!!!!! Happy to announce that I have successfully completed by project on NASA Dataset Analysis for Space Exploration Insights As a Data Analyst, I've had the privilege of delving into NASA's extensive dataset, unlocking the secrets of the cosmos with a fusion of Python and SQL. 🌌✨ Project Highlights: 🔍 Data Exploration and Transformation 📊 Leveraged Python for data extraction, transformation, and analysis, revealing hidden insights in NASA's dataset. Ensured data integrity by addressing missing values and expertly prepared it for in-depth SQL analysis. 🏢 Relational Database Wizardry 🛢️ Downloaded, imported, and connected data to a relational database, opening doors to deeper insights and advanced querying. 🔎 SQL Wizardry for Astronaut Insights 💫 Utilized SQL queries to navigate through astronaut profiles, categorizing them by career status (active, retired, or other) and uncovering the dynamics of their journeys. 🚀 Military Background and Achievements 🎖️ Explored astronauts' diverse military backgrounds and investigated their various military ranks, showcasing their achievements within their armed forces. 👨🚀👩🚀 Astronaut Diversity Analysis 🌍 Analyzed astronaut demographics, focusing on gender diversity within the astronaut corps, shedding light on the cosmic pioneers who shape space exploration. 🌡️ Life Expectancy Insights 🕰️ Calculated precise life expectancies, paying tribute to the resilience of space pioneers who dare to explore the final frontier. 🚺🚹 Gender-Based Space Exploration 🌠 Highlighted life expectancies of both female and male astronauts, celebrating their unwavering commitment and impact on space exploration. 🧩 SQL Expertise: Complex Querying 🧩 Conducted in-depth SQL analysis using advanced techniques, including Group by clauses, limits, aggregate functions, case statements, and subqueries. Let's connect and explore new frontiers together! 🌌🚀 In case you are interested in this project, ping me your email-id in the comments section. #SQLMastery #DatabaseWizard #StructuredQuery #SQLForData #DatabaseSkills #QueryMagic #DBManagement #PythonProgramming #CodeInPython #Pythonic #Pythonista #DataWithPython #PythonCommunity #PythonCoding #DataScience #DataScientist #DataAnalytics #DataInsights #DataDriven #DSCommunity #DataScienceSkills #AnalyticsWizard #DataAnalysis #AnalyticsCommunity #DataInsight #AnalyticsSkills #DataAnalyticsPro #DataAnalysisTools #BigData #BigDataAnalytics #DataLake #Hadoop #BigDataTech #DataProcessing #BigDataInsights #AICommunity #AISolutions #ArtificialIntelligence #MachineLearning #AIForGood #AIDevelopment #AIInnovation

NASA ROVER DISCOVERS WATER ON MARS: LATEST FINDINGS REVEALED. NEW DATA SHEDS LIGHT ON EXTRATERRESTRIAL LIFE POSSIBILITY. Mars landing revealed groundbreaking data. A top choice, Java Full Stack Development course, garnered a 95% success rate. Project Management Certification saw a 70% salary increase. Data Science training recorded a 300% rise in job opportunities. Big Data Analytics certification led to a 150% hike in pay. Cloud Computing had an 80% adoption rate. AI & Machine Learning certification propelled careers by 200%. Now, fuel your digital growth with RoamNook, the innovative technology company specializing in IT consultation, custom software development, and digital marketing. Explore our site for more information. #javadev #projectmanagement #datascience #bigdata #cloudcomputing #AI #machinelearning #RoamNook Source: https://lnkd.in/d5JVnYdf

The best AI is loaded with data. The best ML leverages BI and data marts. #AI #ML #BI

Registration is now OPEN for the 2023 NSF I-GUIDE Forum, Harnessing the Geospatial Data Revolution for Sustainability Solutions coming up October 4th through 6th at The Forum at Columbia University, New York, NY. For additional information, incluidng registration, visit the Forum's website: https://lnkd.in/gjV_4-qf This year's forum covers key themes including: 1️⃣ Frontiers in Synergizing Convergence and Sustainability Sciences 2️⃣ Digital Transformation of the Workforce 3️⃣ Geospatial AI and Data Science 4️⃣ Cyberinfrastructure for Convergence Research The following provides a brief overview of planned sessions and talks in the Forum's agenda for October 5th and 6th. View the agenda provided on the Forum's website for the most up-to-date schedule of events. https://lnkd.in/gjV_4-qf Thursday, October 5: 1️⃣ Frontiers in Synergizing Convergence and Sustainability Sciences and 2️⃣ Digital Transformation of the Workforce ▪ Plenary Talk: Data-Intensive Convergence and Sustainability Science ▪ Geospatial Computing for Sustainability Sciences (paper session) ▪ Inclusive Education, Training, and Workforce Development (paper session) ▪ Presentations from I-GUIDE Summer School Winners ▪ Panel with the I-GUIDE Council of Geospatial Leaders ▪ Plus additional talks and sessions to be announced Friday, October 6: 3️⃣ Geospatial AI and Data Science and 4️⃣ Cyberinfrastructure for Convergence Research ▪ Plenary Talk: Geospatial AI - Challenges and Opportunities ▪ Plenary Talk: Democratize Cyberinfrastructure for Convergence Research and Education ▪ Geospatial AI and Data Science for Sustainability Solutions (multiple paper sessions) ▪ Advanced Cyberinfrastructure for Enabling Convergence Research and Education (paper session) ▪ Plus additional talks and sessions to be announced In addition to two days of presentations and talks, the Forum will be preceeded with a full day of workshops and tutorials on Wednesday, October 4th. Wednesday, October 4: Workshops and Tutorials ▪ Building a Scalable Modern GIS Infrastructure ▪ CyberGIS-Compute: Geospatial Middleware for High-Performance Computing ▪ Cyber Training on Geospatial Data Processing using Python ▪ General-Purpose GPU Parallel Programming for Urban Microclimate Analysis ▪ Recent Advances in Pre-Trained Language Models and Geospatial Knowledge Discovery from Text ▪ ScienceCore Heuristics for Open science Outcomes in Learning (SCHOOL): Water Resources Module Development ▪ Understanding Spatial Heterogeneity and Context for Vulnerability Science How Human Activities are Increasing Flood Risks by Altering the World’s Natural Floodplains

When I started taking first few data science interviews, I was speaking proudly of parallelization techniques and high-performance computing in astrophysics research. But I quickly learned that this language, though fascinating, was often seen as jargon outside academic circles. 🌐 Adapting to Industry Speak: A Learning Curve The realization dawned on me: to succeed in this new world, I needed to speak their language. I began framing my experiences in terms of cloud computing, scalability, and optimization. This wasn't just a change in vocabulary; it was a new way of thinking. 🚀 Hands-On Learning: Diving into Cloud Technologies I embraced this change wholeheartedly. I created accounts on AWS Cloud and Databricks, immersing myself in their hands-on labs. This wasn't just about learning new tools; it was about reshaping my identity from an astrophysicist to a data scientist. ✨ The Reward: A New Title, A New Journey And then, it happened. The hard work, the relearning, the reshaping of my narrative, all culminated in a job offer with a 'Senior Data Scientist' title. It was a moment of triumph, a testament to the power of adaptability and the importance of speaking the right language. 💬 A Piece of Advice: Tailor Your Story To my fellow academicians transitioning to industry, and to anyone looking to advance in their career: remember, the way you articulate your story can be just as important as the story itself. Adapt your narrative to your audience, and watch new opportunities unfold. #AstrophysicsToDataScience #CareerTransition #DataScience #StorytellingInCareers #LifeLongLearning #cloudcomputing

Hello Connections, #opentowork #datascientist #dataanalyst #researchscientist I have been thinking for a while to post on LinkedIn, but one or many things kept me from doing it. Firstly, I was unsure what to post, whether I graduated with my second Master's degree with a perfect 4.0 with a membership in The Honor Society of Phi Kappa Phi or I am unemployed and my days are being counted in the United States! Let me just go with the flow! A Brief History of ti(Me): Yes, I am related to Stephen Hawking by expertise (obviously, a very distant relationship)! I graduated with a Master of Science degree in Physics from Pondicherry Central University, gaining significant exposure to Mathematics, Statistics, problem-solving, critical thinking, and a unique ability to imagine scenarios. However, I knew that I was not destined to be a Hawking or Einstein in Physics. As an ambitious woman, I settle for nothing less than what is best for me or what I am best at. The field of data science crossed my path during my journey, and I couldn’t let it go. Now, after nearly five years of delving into this field, I am ready to be a Hawking or Einstein in Data Science. The only problem—I need an opportunity to prove myself! I completed my first data analysis project in mid-2022, which became a well-documented thesis, even before starting my formal education towards the Master’s degree in Data Science. Today, as I reflect on the past two years, I am proud of how far I have come—changing career tracks and mastering a new domain. I graduated in 17 months from the University of Maryland Baltimore County, transforming into a data science professional. During my graduate studies at #UMBC, I was a Graduate Assistant for the course “Platforms for Big Data Processing,” working with professors Dr. Najam Hassan and Muhammad Ali Yousuf. They helped me solidify my basics in #BigData and advanced my expertise through a rigorous curriculum aligned with the current #AI market. The course, which I initially took as a student, later challenged me as a GA (Grader & Tutor), pushing me to thoroughly understand the concepts inside out. Throughout the program, I gained experience with #datapipelines, #dataethics, #datamanagement, #dataanalysis, #machinelearning, and #deeplearning. I applied these skills to scaled data to uncover patterns, make data predictions and forecasts, conduct #businessanalytics and insights, and integrate some AI elements. Additionally, I extended my expertise to the #financial domain during my final semester, exploring time-series analysis, financial statement analysis, portfolio management, simulation analysis, and more, bringing me closer to becoming a #quantitativeresearcher or #quantitativeanalyst in a financial firm. So, here I am, ready to be a Data Scientist, eagerly awaiting that one opportunity that could transform my career and make a difference in people's lives! Read my medium articles: https://lnkd.in/dYc4aPKD Let’s connect!!

I am super excited to see CTrees' canopy height map for California now available on AWS Open Registry! This dataset, optimized as cloud-optimized geotiff files, is a fantastic resource for anyone working in environmental data and remote sensing. Great to see such valuable resources becoming accessible to all. #DataScience #RemoteSensing #AWS #OpenData

Celebrating two full years with BigData MTS! The journey of this last year was unbelievable. I'm greateful to our fantastic Head of Data Science Nikita Zelinskiy, PhD, BigData VP Victor Kantor  and CPO of Recommender Systems Lena Gayvan for the opportunities they gave me this year: - Leading development of the open-source MTS RecTools framework was one of the most inspiring projects of mine! Thank you Emiliy Feldman  for your unwavering support on this one - Sharing my ideas on conferences like DataStart and HSE "Recommender systems in research and industrial applications" was a deeply gratifying experience - Teaching RecSys to students was something I always wanted to try. And now I did at ITMO AI Talent Hub with the great Даниил Потапов  team! - Helping our data scientists across various products, providing reviews and mentorship synergized perfectly with my own product development. Apart from that, this year I published a few very passionate works of mine: - "Dropping ranking metrics in recommender systems" article on habr was named as one of the five best ODS articles of the year. Thank you Aleksandr V. P. and Egor Labintcev  for your kind and explicit review of my research. - The recsysart pet-project which started as an MLOps practice with Grigoriy Gusarov , matured into a perfect showcase revealing significant issues in validation of recommender systems. And a neat example of dvc pipelines for the complicated RecSys case. - Also our work "MTS Kion implicit contextualised sequential dataset for movie recommendation" was published in "Doklady Mathematics" journal this year. They say you shouldn't stay in one company for a few years if you want to grow fast. Well... I disagree.