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Ayra
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1st lesson free
- Computer Science
- Computer networks
- IT security
- Machine learning
Machine Learning & Artificial Intelligence with Python, Data Science, Statistical Learning, Practical Model Building and Intelligent Systems
- Computer Science
- Computer networks
- IT security
- Machine learning
Lesson location
About Ayra
I am a third-year B.Tech student in Computer Science and Engineering, specializing in Cybersecurity, with a growing interest in Machine Learning, Artificial Intelligence, and Data Science. I enjoy exploring the mathematical principles behind intelligent systems and applying programming to solve computational problems. My approach emphasizes conceptual clarity, analytical thinking, and practical implementation.
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About the lesson
- Primary
- Junior Cycle
- Transition Year
- +13
levels :
Primary
Junior Cycle
Transition Year
Fifth Year
Sixth Year
Adult education
Bachelor's degree
Master's degree
Diploma
Doctorate degree
Other
Beginner
Intermediate
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Professional
Kids
- English
All languages in which the lesson is available :
English
Machine Learning Fundamentals: Supervised, unsupervised, and introductory reinforcement learning; regression, classification, clustering, features, labels, and the end-to-end ML workflow.
Python for AI and Data Science: Python fundamentals, NumPy, Pandas, Matplotlib, and Seaborn for numerical computing, data manipulation, analysis, and visualization.
Mathematics and Statistics for Machine Learning: Probability, descriptive statistics, distributions, conditional probability, linear algebra fundamentals, vectors, matrices, derivatives, and optimization concepts.
Data Preprocessing and Feature Engineering: Data cleaning, missing-value handling, categorical encoding, feature scaling, outlier analysis, feature selection, and dataset preparation.
Core Machine Learning Algorithms: Linear and logistic regression, decision trees, random forests, k-nearest neighbors, support vector machines, Naive Bayes, k-means clustering, and dimensionality reduction fundamentals.
Model Training and Evaluation: Training, validation, and test sets; cross-validation; overfitting and underfitting; bias-variance trade-off; confusion matrices; accuracy, precision, recall, F1-score, and ROC-AUC fundamentals.
Deep Learning Fundamentals: Neural network architecture, neurons, activation functions, loss functions, gradient descent, backpropagation, and introductory implementation using suitable Python frameworks.
Natural Language Processing (NLP): Text preprocessing, tokenization, text representation, bag-of-words, TF-IDF, sentiment analysis, and introductory language-processing applications.
Computer Vision Fundamentals: Image data preparation, pixel representations, image classification concepts, and an introduction to convolutional neural networks.
Time-Series Analysis: Trend and seasonality, time-based data preparation, forecasting fundamentals, and introductory applications using Python.
Model Interpretability and Responsible AI: Understanding model predictions, feature importance, data bias, limitations, and responsible use of AI systems.
Practical Projects and Deployment Basics: Dataset exploration, exploratory data analysis, end-to-end model development, performance evaluation, saving trained models, and introductory deployment concepts.
Sessions can include coding exercises, worked examples, LaTeX-based notes, assignments, and personalized doubt-clearing. Scheduling is flexible, subject to mutual availability. The aim is to build a sound understanding of the concepts, strengthen independent implementation skills, and establish a foundation for more advanced work in AI, Machine Learning, and Data Science.
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Recommendations
Recommendations come from relatives, friends and acquaintances of the teacher
1
I had a really good experience with Ayra di during my SAT preparation... She explained the concepts clearly and was always patient whenever I had doubts... I especially liked how she broke down difficult questions and explained the logic behind each answer... The sessions were helpful and made my preparation feel more organised... Overall, I had a positive learning experience with Ayra di, and I'd definitely recommend her to other students preparing for the SAT.
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Rates
Rate
- €8
Pack prices
- 5h: €40
- 10h: €80
free lessons
The first free lesson with Ayra will allow you to get to know each other and clearly specify your needs for your next lessons.
- 1hr
online
- €8/h
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