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Discover the Best Private Computer programming Classes in Cheltenham

For over a decade, our private Computer programming tutors have been helping learners improve and fulfil their ambitions. With one-on-one lessons at home or in Cheltenham, you’ll benefit from high-quality, personalised teaching that’s tailored to your goals, availability, and learning style.

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1 computer programming teacher in Cheltenham

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
Trusted teacher: Much of the world's raw data—from electronic medical records to customer transaction histories—lives in organized collections of tables called relational databases. Being able to wrangle and extract data from these databases using SQL is an essential skill within the data industry and in increasing demand. In this two-hour introduction to SQL, you'll get to know the theory and the practice through bite-sized videos and interactive exercises where you can put your new-found skills to the test. SQL is an essential language for building and maintaining relational databases, which opens the door to a range of careers in the data industry and beyond. You’ll start this course by covering data organization, tables, and best practices for database construction. The second half of this course looks at creating SQL queries for selecting data that you need from your database. You’ll have the chance to practice your querying skills before moving on to customizing and saving your results. PostgreSQL and SQL Server are two of the most popular SQL flavors. You’ll finish off this course by looking at the differences, benefits, and applications of each. By the end of the course you’ll have some hands-on experience in learning SQL and the grounding to start applying it on projects or continue your learning in a more specialized direction. Relational Databases Before writing any SQL queries, it’s important to understand the underlying data. In this chapter, we’ll discover the role of SQL in creating and querying relational databases. Using a database for a local library, we will explore database and table organization, data types and storage, and best practices for database construction. Querying Learn your first SQL keywords for selecting relevant data from database tables! After practicing querying skills in a database of books, you’ll customize query results using aliasing and save them as views so they can be shared. Finally, you’ll explore the differences between SQL flavors and databases such as PostgreSQL and SQL Server.
Information technology · Computer programming
Computer programming
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 Cheltenham evaluate their Computer Programming teacher.

To ensure the quality of our Computer Programming teachers, we ask our students from Cheltenham to review them.
Only reviews of students are published and they are guaranteed by Apprentus. Rated 5.0 out of 5 based on 16 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
Mathematics and Physics Preparation for High-school (Kortenberg)
David
Punctual and ready to adapt and adjust lessons to my daughter's concerns and needs in math. Highly recommended.
Review by JAMES