IBM Cybersecurity Analyst
Currently working through the IBM Cybersecurity Analyst program, building skills in threat detection, SOC workflows, digital forensics, and modern defensive security.
Hi, I’m Piyush 👋
I explore science and technology to find the patterns that link them, using code and experimentation to deepen my understanding of how systems work.
About Me
Quick facts
Age: 18 • High School (Grade 12) • Majors: Math, Physics, Chemistry
🐍 Python
💻 C / C++
📈 TypeScript / Web
📊 Data Science
🤖 ML
🧠 Neural Networks
🔧 Embedded
🧮 Math
🧪 Physics
🧬 Chemistry
🗣️ 4 Languages
Bio
I’m naturally curious and like to figure things out on my own. Give me an abstract problem or a tricky bit of code, and I’ll dive right in. I love building algorithms, tinkering with machine learning models, and spotting patterns in math and physics. Most of my projects end up as a mix of code, data, and a dose of scientific thinking.
Ever since I was a kid, I’ve wanted to know how things work,whether that meant scribbling out equations, running little experiments, or messing around with simulations. That curiosity turned into a habit: now I approach learning and research with a clear, practical mindset.
When I’ve got some free time, you’ll usually find me working on a new ML project, digging into advanced math or physics, jumping into coding challenges, or helping friends out with math and STEM questions.
Timeline
• AI Sketch Predictor
• Harvard's CS50 courses
• Physics & Chemistry Olympiads
• Machine Learning Crash Course (Google
Developers)
• AI / ML Prompt Engineering
• Kaggle – Data Science / Python Projects
• Harvard PH125.x Data Science Series
... and much more !
Projects & Progress
All
Completed
Ongoing
Ideas
PyTorch
Mastering deep learning, neural networks, tensors, and model training.
CompTIA A+ 220-1201
Studying PC hardware, operating systems, and core IT troubleshooting skills.
Statsmodels Models
Building and analyzing regression models using the statsmodels library.
Scikit-learn Models
Building various ML models using scikit-learn, including regression, classification, and ensemble methods.
Data Visualization in Python
Mastered plotting with Matplotlib, Seaborn, and Plotly Express.
Linux Fundamentals
Acquiring expertise in shell commands, permissions, and system tools.
Data Visualizer App
Planning an interactive Kivy application for plotting and visualizing data.
Arduino Laser Engraver
Designing an Arduino-controlled device to engrave drawings with a laser.
Harvard PH125.x
Completed coursework in ML, statistics, R programming, and data analysis.
Chemistry Olympiad 2026 Preparation
Intensive study across organic, inorganic, and physical chemistry topics.
Physics Olympiad 2026 Preparation
Prepared advanced topics from mechanics to relativity for the competition.
Excel Macros & VBA – Simplilearn
Mastered Excel automation, macro creation, and VBA scripting.
IBM AI Fundamentals
Completed foundational training on AI, machine learning basics, and neural nets.
CS50 R – Introduction to Programming with R
Learned R fundamentals, data manipulation, and strong visualization techniques.
Data Visualization in Python
Mastered plotting with Matplotlib, Seaborn, and Plotly Express.
CS50SQL – Introduction to Databases
Gained hands-on proficiency in SQL and database fundamentals.
Yale Financial Markets
Completed core studies in finance, investment instruments, and market operations.
Data Fundamentals – IBM SkillsBuild
Learned core principles for effective data analysis, management, and handling.
Google Developer ML Foundations
Completed foundational course on machine learning concepts and model implementation.
Prompt Engineering – Learn Prompting
Learned advanced techniques for designing effective and optimized AI prompts.
OSINT – Basel Institute on Governance
Gained proficiency in advanced OSINT strategies and investigative analysis.
Introduction to OSINT – Security Blue Team
Explored OSINT tools, digital footprinting, and anonymization best practices.
Machine Learning Crash Course
Completed Google’s ML course, including hands-on exercises and TensorFlow.
AI Sketch Predictor
Built an AI app that uses a custom neural network to predict user doodles.
Gestura – Concept & Plan Phase
Designed a smart-ring system concept translating gestures into speech via ML.
Bundeswettbewerb Mathematik
Participated in the national math competition, focusing on advanced proofs.
CS50p – Introduction to Python
Completed the Python-focused CS50 course with practical projects and exercises.
Bundeswettbewerb Informatik
Competed in the national informatics competition, solving complex algorithmic problems.
CS50x – Introduction to Computer Science
Completed Harvard’s full CS50x course, covering C, algorithms, and core CS principles.
Physics Olympiad 2025 – 1st Round
Solved advanced Olympiad problems across mechanics, EM, and quantum physics.
Chemistry Olympiad 2025 – 1st & 2nd Round
Advanced through Olympiad rounds in organic, inorganic & physical chemistry.
Learning & Knowledge Base
Current Learning
Mathematics
90%
Physics
85%
Chemistry
80%
Machine Learning & AI
75%
Data Science
70%
Python Programming
80%
Prompt Engineering
75%
Linux
10%
OSINT
35%
Finance & Markets
60%
Embedded Systems
65%
Languages
85%
Neuroscience
5%
Resources
- 📚 University Physics with Modern Physics, 15th Edition – Hugh D. Young
- 📚 The Feynman Lectures on Physics
- 📚 A Book of Abstract Algebra – Charles C. Pinter
- 📚 The Algebra – Serge Lang
- 📚 Introduction to Topology – Bert Mendelson
- 📚 Chemie Basiswissen – Charles E. Mortimer
- 📖 Neuroscience for Dummies
- 📖 Kotler and Armstrong – Principles of Marketing
- 📖 The 48 Laws of Power – Robert Greene
- 📖 The Personal MBA – Josh Kaufman
- 📖 New Practical Chinese Reader– Peipei Yan
- 💻 Harvard Online Courses
- 💻 MIT Online Courses
- 💻 IBM Courses
- 💻 CompTIA Courses
- 🌐 Kaggle Resources & Datasets
- 🌐 Google Colab Resources
Learned Topics
🧮 Mathematics
- Linear Algebra: Vector spaces, matrices, eigenvalues, linear transformations.
- Calculus & Analysis: Derivatives, integrals, multivariable calculus, series, convergence.
- Probability & Statistics: Random variables, distributions, expectation, limit theorems.
- Abstract Algebra: Groups, rings, fields, homomorphisms, basic structures.
- Topology: Metric spaces, open/closed sets, continuity, compactness.
⚛️ Physics
- Classical Mechanics: Newtonian dynamics, conservation laws, oscillations, wave motion.
- Electromagnetism: Electric & magnetic fields, Maxwell’s equations, circuits, optics.
- Quantum Physics: Wave functions, operators, quantization, atomic models.
- Relativity: Special relativity, Lorentz transformations, time dilation & length contraction.
- Thermodynamics & Statistical Physics: Laws of thermodynamics, entropy, distributions.
🧪 Chemistry
- Organic Chemistry: Mechanisms, stereochemistry, spectroscopy (IR, NMR).
- Inorganic Chemistry: Periodic trends, coordination chemistry, crystal field theory.
- Physical Chemistry: Thermodynamics, kinetics, quantum chemistry basics.
- Analytical Chemistry: Titrations, chromatography, UV-Vis and MS analysis.
- Laboratory Skills: Synthesis, purification, spectroscopy, safe lab practice.
💻 Computer Science
- Python: Scripting, data analysis, automation, scientific computing.
- Java & TypeScript: Application development, object-oriented design, frontend basics.
- Algorithms & Data Structures: Sorting, searching, trees, graphs, complexity analysis.
- Databases: SQL, relational modeling, MySQL/PostgreSQL fundamentals.
- Prompt Engineering: Effective prompting, task decomposition, optimization strategies.
🤖 Machine Learning & AI
- Supervised & Unsupervised Learning: Regression, classification, clustering.
- Neural Networks: Feed-forward networks, CNNs, training fundamentals 🧠.
- Data Processing: Cleaning, feature engineering, normalization, visualization 📊.
- Model Training & Evaluation: Loss functions, optimization, metrics, validation.
📊 Data Science & Visualization
- Data Cleaning & Processing: Pandas, NumPy, handling missing values 🐍.
- Visualization: Matplotlib, Seaborn, ggplot-style plotting, clear data narratives 📈.
- Statistical Foundations: Distributions, inference, correlations, variability.
- Exploratory Data Analysis: Pattern detection, feature insights, summary reports 🔍.
🛡️ OSINT & Cybersecurity
- OSINT Techniques: Open-source data gathering, verification, digital footprint analysis.
- Cybersecurity Basics: Privacy, anonymization, threat awareness, secure practices 🔒.
- Investigation Methodologies: Structured searches, evidence tracing, information validation.
💰 Finance & Markets
- Financial Markets: Market structure, asset classes, price formation.
- Investing & Risk: Portfolio basics, diversification, risk-return principles.
- Quantitative Finance: Data-driven analysis, indicators, financial modeling.
Achievements & Recognition
0
Projects completed
0
Awards & certificates
17
Books studied
0
STEM competitions
Certificates & Achievements
All
CS50
Kaggle
IBM
Olympiad
Competition
AI & ML
OSINT
CS50x – Introduction to Computer Science
Harvard • CS
Foundational computer science with C, algorithms, data structures, web development, and logic.
CS50P – Programming with Python
Harvard • Python
Comprehensive Python training with debugging, object-oriented concepts, scripting, and practice.
CS50 SQL – Databases with SQL
Harvard • SQL
Working with relational databases through SQL queries, schema design, joins, constraints, and logic.
CS50R – Programming with R
Harvard • R
Fundamental R skills covering data handling, visualization, statistics, and computation.
CS50R – Programming with R
Harvard • R
Fundamental R skills covering data handling, visualization, statistics, and computation.
Kaggle – Intermediate Machine Learning
Kaggle • ML
Applied machine learning with XGBoost, pipelines, model validation, and handling data issues.
Kaggle – Feature Engineering
Kaggle • ML
Transforming raw datasets into structured, valuable, and high-impact features for stronger models.
Kaggle – Time Series
Kaggle • ML
Forecasting using trends, seasonality, autocorrelation, and essential practical time-series models.
Kaggle – Introduction to Machine Learning
Kaggle • ML
Core ideas of supervised learning, training predictive models, bias, and evaluating accuracy.
Kaggle – Python
Kaggle • Python
Practical Python exercises covering scripting, automation, data analysis, and core programming concepts.
Kaggle – Pandas
Kaggle • Data
Data manipulation, cleaning, grouping, and transformation techniques using the powerful pandas library.
Kaggle – Data Visualization
Kaggle • Data
Building clear and expressive data visualizations with Matplotlib and Seaborn for analytical insights.
Kaggle – Introduction to Programming
Kaggle • CS
Programming foundations in Python including loops, logic, debugging, variables, and basic problem solving.
Artificial Intelligence Fundamentals
IBM • AI & ML
Modern AI concepts including ML models, neural systems, automation, and decisions.
Data Fundamentals
IBM • Data
Foundational concepts in data lifecycle, analytics, architecture, databases, sorting, and organizational value.
Machine Learning Crash Course
Google • AI & ML
Applied ML using TensorFlow, focusing on gradient descent, regularization, and projects.
IPhO 2025 – 1. Runde
Competition • Physics
Challenging physics problems in mechanics, thermodynamics, electricity, and reasoning.
IChO 2025 – 2. Runde
Competition • Chemistry
Challenging national-level chemistry problems requiring high analytical depth, logic, and precision.
IChO 2025 – 1. Runde
Competition • Chemistry
National chemistry probelms requiring graduate , knwoldege and advanced thinking.
Bundeswettbewerb Mathematik
Competition • Math
Olympiad-level mathematical reasoning focusing on rigorous proofs, and abstraction.
Bundeswettbewerb Informatik 2024/25
Competition • CS
Computational challenges involving algorithms, optimization, logic, and structured design.
Jugendwettbewerb Informatik 2025
Competition • CS
National informatics contest testing algorithmic thinking, structured logic, creativity, and strategy.
Informatik - Biber 2022
Competition • CS
Logic-based informatics puzzles focusing on pattern recognition, abstract reasoning, and structured thinking.
Jugendwettbewerb Informatik 2022
Competition • CS
National junior contest exercises emphasizing algorithmic reasoning, abstraction, and computational logic.
Informatik-Biber 2021
Competition • CS
Introductory informatics problems focused on abstraction, pattern recognition, and abstract reasoning.
Krypto im Advent 2021
Challenge • CS
Daily cryptography challenges covering ciphers, logical deduction, codes, and abstract analysis.
OSINT – Basel Institute on Governance
Basel Institute • OSINT
OSINT research methods focusing on digital tracing, verification, and investigation.
OSINT – Security Blue Team
Security Blue Team • OSINT
Applied OSINT workflows for footprinting, adversary mapping, reconnaissance, and analysis.
ChatGPT for Everyone – Learn Prompting
OpenAI • Prompting
Prompt engineering strategies for improving AI reasoning, creativity, usefullnes and clarity.
Personal Updates
🚀 Microsoft Imagine Cup Participant
Dec 2025 • AI & Cybersecurity
Currently developing an AI-driven security system that analyzes user behavior patterns—such as login times, file access, data transfers, and locations—to identify anomalies and flag potential breaches before they occur.
🛡️ IBM Cybersecurity Analyst
Nov 2025 • Cybersecurity
Recently began the IBM Cybersecurity Analyst program, gaining foundation-level skills in digital security, threat detection, incident response, and modern defense practices.
🧠 Neuroscience Learning
Nov 2025 • Neuroscience
Currently exploring the fundamentals of neuroscience, understanding how the brain processes information and controls behavior.
🐧 Linux
Nov 2025 • System Administration
Currently learning Linux commands, file management, and shell scripting. Enjoying the process of understanding the system from the inside out.
🕵️ Cybersecurity & Ethical Hacking
Nov 2025 • Security Skills
Actively practicing ethical hacking, vulnerability scanning, and network security techniques. Learning how to identify and mitigate security risks in real time.
📊 Data Visualization App
Nov 2026 • App Development
Planning to build an interactive app that visualizes datasets with charts and graphs. The goal is to make data exploration engaging and intuitive.
🪵 Wood Engraving Arduino Project
Oct 2025 • Embedded Project
Planning an Arduino-controlled wood engraving machine. Excited to combine electronics, coding, and hands-on craftsmanship in a creative project.
🧪 Chemistry Olympiad Qualification
Oct 2025 • Competition
Qualified for the next round of the International Chemistry Olympiad. Looking forward to solving more challenging chemistry problems.
⚛️ Physics Olympiad Qualification
Oct 2025 • Competition
Achieved qualification for the International Physics Olympiad. Excited to tackle advanced physics problems and refine problem-solving skills.
🎓 DPG Schülertagung
Sep 2025 • Physics Conference
Attended the student physics workshop and presented a small topic. Great opportunity to connect with other students and exchange ideas.
🤖 ML Models via Scikit-learn, Statsmodels, TensorFlow & Keras
Sep 2025 • Machine Learning
Currently developing and testing machine learning models for regression and classification tasks. Exploring how models learn from data in real time.
Contact & Connect
Let’s connect! I enjoy discussing STEM, AI, and innovative projects.
LinkedIn • GitHub • Credly • Google Developers • Email
Feel free to reach out for collaborations, questions, or a chat about tech.