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Database lessons in Yakuplu

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1 database teacher in Yakuplu

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1 database teacher in Yakuplu

What am I teaching? Python 3 programming with libraries: Pillow, PyQT, Pygame, SQLite/MongoDB, Flask + SQLAlchemy, NumPy, Pandas, Sklearn HTML and CSS basics due to the Web-programming topic (Flask) SQl/NoSQL (MySQL and PostgreSQL and MongoDB) due to the SQLite/MongoDB library What does it mean? Python is a powerful tool for basic algorithmic tasks, projects with images/sounds/..., web development, data science and so on. I would be glad to learn you in a practical way to use these tools to solve ample different tasks. Information about me: - I am 3rd-year student in ITMO University (Software engineering and programming) - I'm teaching Python for more than 2 years - My students succeeded with their Python exams (100% passed) - I have 5 years experience with Python programming language and get several certificates: Python Basics and Projects (excellent mark) from Yandex Lyceum, Python in Industry programming (excellent mark) from Yandex Lycuem, Advanced Python (Stepik online cource) - English level (B2-C1), Swedish (A2-B1), Russian (native) Teaching features: - All topics I explain clearly with ample comparisons to real life - After every piece of information I'm checking student's understanding (asking similar questions to discuss) - All lessons are split into 2 vital parts: discussing new topics and practicing coding - Basics projects after each module Three ways of learning: - Basic track: Module 1 - Basics: installing/if/else/for/while Module 2 - Data Structures: lists/sets/dicts Module 3 - Functions: def Module 4 - Libraries: math/os/pillow/... Module 5 - OOP: classes/methods - Advanced track: Module 1 - Revicing: data structures and OOP Module 2 - Advanced topics: itherators/try/except Module 3 - PyQT Module 4 - Web-programming Module 5 - API and Applied Projects - Custom track: Possible topics: All in Basic and Advance tracks, Numpy, Pandas, Sklearn - Data Analysis basics What is the format of teaching: Online
Computer programming · Python · Database
Trusted teacher: I offer courses in data development / database / machine learning / data science (python): I also offer the possibility of helping you with the realization of your academic projects. We support you in the Data development of your business. -1- Databases & Data warehouses (AWS / Google Cloud / Azure Cloud) -2- Machine Learning -3- Deep Learning (tensorflow, pytorch, RNN, CNN, LSTM) -4- Data Processing -5- Machine Learning design and deployment (docker, ...) -6- Data Pipelines -7- Google Sheets with Realtime Pipelines, Macro (VBA) & Database Connection -8- Online dashboards on browsers or on your Excel, Google Sheets (Python, R, Power BI, Tableau, Kibana, etc.) - Our Tech Stack - - Databases: AWS DynamoDB, Amazon Redshift, PostgreSQL, MySQL, multi-cube DBs (EPM / BI platform) - Languages: Python, Spark (Scala, Python, Java), JavaScript, CSS, HTML - Development environment: JSON, SQL, NoSQL, Bash Shell Scripting, Jupyter Notebook, Anaconda, REST API, VSCode, DBeaver, Google services, Platform as a Service (PAAS), Apache Airflow, Serverless Computing, SublimeText - Clouds: Amazon Web Services, Azure Databricks, Google GCP (Google Firebase) - Data Lake AWS / Databricks: EC2 (Linux), IAM, Amazon MWAA (Managed Workflows for Apache Airflow), Lambda, S3, DynamoDB, RedShift; Kibana, Azure Databricks, CloudFormation - Web crawling / Scraping: Python Scrapy - Data streaming: Airflow, Kafka - Data visualization / ETL: Python, Kibana, Tableau, Power BI & DAX, Excel Power Query (and lang.M) - Continuous integration workflows (CI / CD): Docker / Google cloud / Kubernetes; Amazon ECS) - Containerized applications: Docker (Docker container, Docker-compose) - Virtualization technologies: VirtualBox, Vmware - Agile tools: Version control (Git / GitLab), tickets (JIRA), Bitbukets, Trello, Wiki (Confluence), Jetbrains - OS: Linux, Windows
Numerical analysis · Information technology · Database
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