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Discover the Best Private Python Classes in Aarhus

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1 python teacher in Aarhus

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1 python teacher in Aarhus

Andrea - Kowloon, Hong Kong£115
£115PhD graduate Data Science, Data Analysis, Quantitative Methods, Python, Matlab, Statistical Packages/Software, Stata, R, Database, SQL, Ora
Trusted teacher: SERVICES I can offer my assistance with Data Analysis, Data Science, Quantitative Methods, Analysis, Statistical Modelling, Forecast, Regression, Coding, Python, Matlab, Excel statistical software and packages such as Stata, R and Database languages such as SQL, Oracle, MySql and other Business-related subjects (with coding and programming if you are interested in it). I understand that there are different kinds of learning methods, so as long as you can find your style and the appropriate method, I believe that you can get twice the result with half the effort. I have been told to be good at breaking down complex statistical and modelling concepts, explaining them in diagrams, and also relating them to their uses in our daily lives. I can help you to understand statistics, econometrics, linear regression, forecast modelling, statistical modelling, quantitative methods, as well as introducing you to the fast-growing field of Data Analysis and Data Science. I can teach how to use Python, Matlab, Stata, R, Sas, R, Excel, SQL, Oracle, MySql and many more. - Statistics - Machine Learning - Deep Learning - Probability - Linear Regression - Statistical Modelling - Analysis - Data Analysis/Science - Modelling - Forecasting model - Time Series Analysis - Quantitative Methods - Python - Matlab - Stata - R - Sas - Excel EXPERIENCE AND EDUCATION - PhD graduate in Finance, with 5 years of research experience and scientific contribution in the field of empirical asset pricing with focus on equity factor models, machine learning for asset pricing, regime switching models, sentiment analysis, and portfolio construction - Freelance tutor and consultant in Finance, Data Science, Python, Statistics, and Econometrics for 3 years with 1500+ hours delivered to 150+ students and customers internationally - Former financial analyst with 4 years of experience in design and realization of prototypes of several financial algorithms of a proprietary software for portfolio management, analysis, and consulting - Experienced in written and oral communication to various audiences, from academic students to financial industry leaders and professionals through reviewing, editing, teaching, consulting, and oral presentations - Former University Teaching Assistant, strong analytical background with extensive classroom and online teaching experience, MSc in Quantitative Finance, Bachelor of Science in Economics and Finance - Excellent material available including slides, videos, tutorials and reading material. Extensive experience in research methods and software including Python, Jupyter notebook, Matlab, Sas, Stata, R, SQl/Oracle and Excel. - I thoroughly enjoy helping others, as my patience and friendly nature makes it easier to be in an educational environment. - I have learnt to adapt to different needs and learning styles according to the student, in order to optimise their success in turning their weaknesses into strengths. - I'm patient, friendly and understanding. I am proficient in research and development and it’s my day to day work. I am a photography enthusiast and an insatiable learner. GREETINGS My goal is also to inspire further study that will lead to an interesting and successful career. If you need further information about myself or my services, please do not hesitate to contact me. Feel free to send me a message and I'd be happy to give you an informal consultation. Thank you for looking at my profile and hope to hear from you soon, Andrea
Database · Python · Computer programming
Jhosimar - Peru£23
£23Private or group classes of Machine Learning and Deep Learning
Trusted teacher: Master in Computer Science from the State University of Campinas (Brazil) and university professor in Peru. He has participated in the most important Artificial Intelligence conferences including ACL, NeurIPS, ICML, ICLR, KDD, ICCV and CVPR, summer schools such as Machine Learning (MLSS), Deep Learning (DLRL) and Probabilistic ML (ProbAI). He has also participated in various programming contests and has experience preparing interviews for applications to companies such as Google, Meta, Microsoft, among others. He has extensive experience in the areas of Machine Learning and Deep Learning applied mainly to computer vision and natural language processing. He has experience in teaching, providing illustrative explanations for a better understanding of both the theoretical and practical parts. Some examples of presentations given: - He has also advised students from different countries in their graduation and master's theses, providing them with a theoretical and practical base with examples that they can then use to continue their development. Some of the things I can help you with: - Machine Learning: Linear regression, logistic regression, regularization, LDA, QDA, SVMs, decision trees, random forest, boosting, PCA, clustering (K-means, DBSCAN, hierarchical, GMM), neural networks, model selection, metrics evaluation, MLE, Bayesian learning, data preprocessing, etc. - Deep Learning: Multilayer Perceptron (MLP), backpropagation, activation functions, multiclass classification, optimizers (SGD, Adam, RMSProp, etc.), CNNs, architectures (ResNet, DenseNet, EfficientNet, Siamese, etc.), RNNs, LSTMs, Seq2seq, Attention, Transformers (BERT, GPT, ViT, etc.), autoencoders, generative models (VAE, GAN, Diffusion, etc.), etc. - Languages: Python, C++ - Libraries and frameworks: PyTorch, Tensorflow, Keras, Huggingface, numpy, pandas, scikit-learn, sympy, etc.
Computer programming · Python
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Mourad - Canada£21
£21Machine Learning with Python and PyTorch: Practical Hands-on Training
Trusted teacher: Welcome to "Machine Learning with Python and PyTorch: Practical Hands-on Training," a beginner-friendly course designed to introduce you to the exciting world of machine learning using two of the most popular tools in the industry: Python and PyTorch. This course focuses on practical, hands-on learning, ensuring you gain the skills needed to start building your own machine learning models. #### Course Objectives: - **Introduction to Machine Learning:** Understand the basic concepts and principles of machine learning. - **Python Programming for Machine Learning:** Learn Python programming essentials tailored for machine learning applications. - **PyTorch Fundamentals:** Get acquainted with PyTorch, a powerful and flexible deep learning framework. - **Practical Experience:** Gain hands-on experience by working on real-world projects and exercises. - **Model Building and Evaluation:** Learn to build, train, and evaluate various machine learning models. #### Course Outline: 1. **Introduction to Machine Learning:** - What is machine learning? - Types of machine learning: supervised, unsupervised, and reinforcement learning - Applications of machine learning in different industries 2. **Python Programming Essentials:** - Introduction to Python programming - Data structures and libraries (NumPy, Pandas) - Basic data manipulation and visualization (Matplotlib, Seaborn) 3. **Getting Started with PyTorch:** - Introduction to PyTorch and its ecosystem - Setting up your environment and installation - Understanding tensors and basic tensor operations 4. **Building Your First Machine Learning Model:** - Data preprocessing and preparation - Splitting data into training and testing sets - Building a simple linear regression model with PyTorch 5. **Training and Evaluating Models:** - Understanding the training process - Loss functions and optimization algorithms - Evaluating model performance using metrics 6. **Advanced Models and Techniques:** - Introduction to neural networks - Building and training a neural network with PyTorch - Exploring convolutional neural networks (CNNs) for image classification 7. **Practical Projects and Applications:** - Hands-on projects to reinforce learning - Real-world applications and case studies - Tips and best practices for successful machine learning projects 8. **Next Steps in Your Machine Learning Journey:** - Exploring further learning resources - Joining machine learning communities and forums - Preparing for advanced topics and courses #### Who Should Enroll: - Beginners with no prior experience in machine learning - Individuals interested in learning Python programming - Aspiring data scientists and machine learning enthusiasts #### Prerequisites: - Basic computer literacy and familiarity with high school-level mathematics - No prior programming or machine learning experience required #### Course Outcomes: By the end of this course, you will be able to: - Understand the fundamental concepts of machine learning - Write and execute Python code for machine learning tasks - Use PyTorch to build, train, and evaluate machine learning models - Apply your knowledge to real-world problems and projects - Take the next steps in advancing your machine learning skills Join us in "Machine Learning with Python and PyTorch: Practical Hands-on Training" to embark on your journey into the fascinating world of machine learning. Gain the skills and confidence needed to build and deploy your own models, and start making an impact with machine learning today.
Python · Computer programming
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Our students from Aarhus evaluate their Python teacher.

To ensure the quality of our Python teachers, we ask our students from Aarhus to review them.
Only reviews of students are published and they are guaranteed by Apprentus. Rated 5.0 out of 5 based on 6 reviews.

Learn Python - from the basics to real world business cases (Amsterdam)
Joris
Joris is super friendly and was really flexible in tailoring the classes based on what my purpose for learning is. He is giving me the direction I need to continue this learning journey, and I would certainly recommend him to anyone interested in learning python to the next level.
Review by SEBASTIAN

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