Hello! I'm a computer scientist and mathematician, and as a lover of languages and literature, I'm currently studying Hispanic Philology. I'm a teacher and have experience teaching math classes up to high school, as well as introductory programming, database programming, and databases. I can come to your home or teach online. Hello! I have a background in Computer Science and Mathematics and, as a lover of languages and literature, I am currently studying Hispanic Philology. I am a teacher with experience teaching Mathematics up to high school level, as well as introductory programming, programming with databases, and database management. I can offer lessons at home or online.

I will need everyone to understand how tech works before SQL, PHYTHON, AWS, AI or DevOps and so much more. in a quest, to understanding how tech works, everyone is expected to learn the basics because it’s all interwoven. I specialised in tutoring and mentorship of SQL and some widely used database systems from beginners level. my goal is to ensure the steps to steps build up in taught well and tutor you to become a confident professional. I am more interested in guiding you through your tech journey, you will be pleased to learn a lot about assessing and data manipulation and so much more you could to do with Sql.

When creating a Machine Learning Model languages like julia, R, or Python is compulsory, and for analysis statstics and maths must be learned.Apart from this Data importing and cleaning of Data is also important and for that getting data from database and learning the behaviour of data is important. I Can help you start from the scratch by helping you with working on real world projects.

I am an experienced computer science teacher with many years of teaching experience and a university degree in Mathematics and Computer Science. I offer individual online lessons in programming and computer science for school students, as well as support for university students in selected subjects. Lessons can cover Python, MATLAB, SQL and databases, algorithms and programming fundamentals, computer systems, and web development with HTML, CSS and JavaScript. My lessons are adapted to each student's previous knowledge, current curriculum and individual goals. I explain concepts step by step and focus on understanding the logic behind programming rather than simply memorizing code. We can work on current school or university topics, programming exercises and assignments, fill gaps in knowledge, prepare for tests and exams, or develop practical programming skills. Lessons are taught online in Serbian, Bosnian or Croatian, which can be particularly helpful for students from families from the former Yugoslavia who live and study in Germany, Austria, Switzerland or other countries.

Learn how to create impactful marketing campaigns by combining data insights with effective communication strategies. This class will teach you to analyze customer data, identify trends, and design campaigns that resonate with your audience while delivering measurable results. Perfect for anyone looking to elevate their marketing efforts.

I offer engaging and comprehensive programming lessons in C++ and Python, designed to help you master essential concepts and advanced topics in computer science. From problem-solving techniques, object-oriented programming, and data structures to database management, operating systems, digital logic design, and algorithm analysis, my lessons cover it all. I also introduce exciting areas like parallel and distributed computing and the basics of artificial intelligence. Whether you're preparing for GCSEs, A-levels, or pursuing a BSc in Computer Science, my tailored approach ensures you build a strong foundation and advance to becoming an exceptional programmer. Let’s make programming both accessible and enjoyable as you unlock your full potential in this ever-evolving field!

I specialize in tutoring programming and software development, with a focus on Java, Spring Boot, Angular, SQL. My goal is to help students build a strong understanding of programming while keeping lessons practical, engaging, and appropriately challenging—not overwhelming. This class is designed for students and aspiring developers who want to strengthen their programming skills or start their journey in software engineering. We can work on programming fundamentals, web development, databases, APIs, backend and frontend development. I use practical examples and hands-on exercises to help you understand concepts and apply them to real-world projects.

Welcome to "AI and Data Science" – a comprehensive, customizable course designed for learners at any level, from beginners to advanced professionals. Whether you're just starting your journey into the world of artificial intelligence and data science or looking to enhance your existing skills, this course will provide you with the knowledge and practical tools you need to excel. What You'll Learn: Fundamentals of Data Science: Understanding data collection, cleaning, and preprocessing; learning to analyze and visualize data using tools like Python, Pandas, and Matplotlib. Introduction to AI and Machine Learning: Explore basic concepts of AI, supervised and unsupervised learning, and popular algorithms (e.g., regression, classification, clustering) with hands-on coding exercises. Advanced AI Techniques: Delve into deep learning, neural networks, and advanced algorithms like decision trees, SVMs, and reinforcement learning. Practical Projects: Work on real-world projects such as predictive modeling, sentiment analysis, and building AI applications using Python libraries like TensorFlow and PyTorch. Storytelling with Data: Develop skills to communicate insights effectively, using data visualization tools and storytelling techniques to create compelling narratives from data. Database Management: Learn how to work with databases (SQL and NoSQL) and manage data efficiently for large-scale applications. What to Prepare: Basic Computer Skills: No prior programming experience is required for beginners, but familiarity with basic computer operations is recommended. Software Setup: Students will need to install software like Python, Jupyter Notebooks, and data science libraries (instructions will be provided during the course). Curiosity and Dedication: This course encourages a hands-on approach, so students should come ready to code, experiment, and learn through practical examples. What to Expect: Customized Learning Experience: Lessons are tailored based on the student’s level and goals, ensuring a personalized approach that aligns with your learning pace and interests. Supportive Environment: Receive one-on-one mentoring and support to help you overcome challenges and master complex topics. Skills You Can Apply Immediately: Gain practical, job-ready skills that are in high demand across industries, including AI, finance, marketing, and tech.

This course provides a comprehensive introduction to the core principles of Computer Science, with a focus on practical applications in Computer Programming and Database Management. Students will explore the fundamentals of programming, learning how to write, analyze, and debug code using modern programming languages. The course also delves into database concepts, covering data storage, retrieval, and management techniques. By the end of the class, students will be equipped with the skills necessary to design efficient programs and manage databases effectively, preparing them for more advanced studies in computer science and related fields.

Data Mining Algorithms and Techniques Training Course - Beginner and Intermediate Level, for Computer Science Professionals and Non-Professionals. The course content is titled: Advanced Analysis and Data Mining. The book can be searched for using its name or the author's name. Table of Contents Chapter 1: Introduction to Advanced Analysis and Data Mining 1-1 What is data mining, its procedures and tools 1-2 What type of data is mined? 1-3 What are databases? 1-4 Relational Database 1-5 Query Language 1-6 Benefits of Database Mining 1-7 months data mining applications A - Business Intelligence (Business Intelligence) B - Internet search engines Chapter Two: Data Recognition 2-1 Data Types, Characteristics, and Features 2-2 Statistical Description of Data 2-3 Visualization of Data 2-4 Measuring data similarity and difference Chapter Three: Preparing Data for Analysis and Mining 3-1 The importance of preparing data for analysis and mining 3-2 Data Cleanup 3-3 Data Integration 3-4 Data Reduction 3-5 Data Transformation and Data Individualization Chapter Four: Pattern Discovery and Exploration, Dependency and Correlation Rules 4-1 Basic Concepts 4-2 Shopping basket analysis (example) 4-3 Evaluating the dependency and correlation rules being explored 4-4 Mining Multi-Level Dependency and Linkage Rules 4-5 Mining multidimensional dependency and correlation rules 4-6 Rules of nominal and quantitative dependency and correlation 4-7 Exploring and identifying rare and negative patterns 4-8 Exploring and Determining the Rules of Dependency and Conditional Linkage 4-9 Evaluating dependency and correlation rules and distinguishing between useful and unhelpful ones 4-10 Measuring the type and strength of the relationship in dependency and correlation rules 4-11 Applications of pattern mining in practical life Chapter Five: Analysis and Mining Using Classification and Prediction Algorithms 5-1 Basic Concepts 5-2 Classification using decision tree extrapolation 5-3 Classification using probability theory (hypothetical theory) 5-4 Classification using hypothetical network theory 5-5 Classification using correlation rules extrapolation 5-6 Classification using neural network algorithm 5-7 Classification using the nearest neighbor algorithm 5-8 Multi-category classification algorithms 5-9 Evaluating the efficiency and selection of classification algorithms Chapter Six: Analysis and Mining Using Cluster Hashing Algorithms 6-1 Basic Concepts 6-2 Clustering by Division 6-3 Hierarchical Clustering A. Hierarchical clustering b. Hierarchical fission 6-4 Probability Clustering 6-5 High-Dimensional Clustering 6-6 Clustering of graphs and network data 6-7 Conditional Clustering 6-8 Cluster Segmentation Assessment Chapter Seven: Analyzing and Mining Outliers and Complex Data Types 7-1 Basic Concepts 7-2 Types of extreme values 7-3 Ways to Explore Extreme Values 7-4 Complex Data Analysis and Mining Chapter Eight: Planning Data Mining Operations and Their Applications in Society 8-1 Planning Data Mining Operations 8-2 Data Mining in the Community 8-3 Data mining applications in vital areas of society 8-4 Practical Application: Recommendation System Usage Scenario Appendix 1: Database Fundamentals Appendix 2: Data Warehouse Fundamentals Appendix 3: Glossary of Data Mining Terms

Computer science is a broad field, so I can teach computer programming languages, Data base, operative system, computer networking, C++, C#, Front-end designing computer basics, and other subjects related to computer science or information technology.

Python is a powerful language to deal with different types of data and web applications. As a Python developer, you will need to be able to start learning python from basic to advance that will help make you a industry demanding person. I have designed this course as a practical guide to Python that specially made for Future Python developers. You will learn variables, data types, type casting, selection statements, iterative statements, functions, OOP, recursion, pandas, NumPy, matplotlib, data science, data cleaning, data preprocessing, data analysis, machine learning and much more.

Learn Microsoft Excel from Basic to Advanced from a Microsoft Excel MVP. In my bespoke Excel training, I cover all the key topics that everyone who uses Excel must know such as using 1. Basic Formulas and Functions. 2. Applying General Formatting to Dataset. 3. Applying Freeze Panes and Split Windom 4. Analysing Data using PivotTable and PivotCharts 5. Using VLOOKUP, XLOOKUP, INDEX/MATCH and CHOOSE Functions

Data Science can be learned in a better way if you have an understanding of practical problems that are to be worked on. I focus more on explaining the concept behind a certain topic while taking real-life examples, which not only helps in understanding the topic but also makes the student industry ready. Moreover, I help with career counselling and transition towards Data Product Manager, DS, Quant and ML/AI engineer.