Computer Science software architecture, Data science

Van 71.97 $ /h

Some students will know how to use technology tools (such as texting) better than their teachers. But to really understand computing, including the science behind it and the ways to manipulate it, students need to take classes related to computer science taught by certified teachers who can express themselves well and who may have worked in the computing field before they became educators.

In addition to explaining the fundamentals of computing, these teachers will be showing their students the merits of problem-solving, collaboration, and creativity.

It’s a challenging and rewarding profession. Computer science teachers are always looking forward. They keep their eyes on the latest advances, the newest tools and breakthroughs. And they always keep the future in mind while teaching because, if they do their job right, some of their students may be inspired to become tomorrow’s engineers, system administrators, and innovator.

Locatie

Online vanuit Pakistan

Over

Understanding the science behind computer science, or computing, can tell us about our past and our future. From abacuses and calculators to mainframes, laptops, and smart phones, computing has transformed our world and makes our lives easier in many ways.
I am here to help you by answering your Questions.

Opleiding

Matriculation in science (Chemistry,Maths,Biology,physics)
Intermediate in Pre Engineering(Maths)
Bachelors in software Engineering
Master in Software Engineering

Leservaring

Teach computer science in Scholar science collage
Teach Computer science in kip evening coaching
front end web developer at Iplex software house

Leeftijd

Peuters (0-3 jaar oud)

Kleuters (4-6 jaar oud)

Kinderen (7-12 jaar oud)

Tieners (13-17 jaar oud)

Niveau van de leerling

Beginner

Gemiddeld

Gevorderden

Duur

60 minuten

De les wordt gegeven in

Engels

Vaardigheden

Microsoft office

Computer programmeren

Database

Beschikbaarheid typische week

(GMT -05:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Computer Science, and Test prep Tutoring .Learn how to easily understand computer science by real life examples and solution.

71.97 $ /h

I have done Masters in computer science, I can teach you in a very friendly environment.
A student majoring in computer science must excel in the use of computers, physical sciences, mathematics and English. This student is independent, self-motivated, able to concentrate, and able to handle frustration effectively.
The required and elective courses you would take for Computer Science majors vary considerably among institutions. Courses are listed here that are illustrative of the breadth of topics you are likely to experience were you to major in this field.

Algorithms
Artificial Intelligence
Calculus
Computer Architecture
Computer Science Theory
Computer Theory
Data Logic
Data Management
Design Physics
Device Utilization
Electronic Design
Files and Databases
Information Management
Logic Design
Machine Language
Network Fundamentals
Operating Systems
Programming Languages
Statistics

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HTML / HTML5 – Structure, semantics, forms, accessibility

CSS / CSS3 / SCSS – Layout, animations, responsive design, Flexbox, Grid

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TypeScript – Strong typing, interfaces, decorators, generics

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Vue.js (optional) – Reactive programming, lifecycle management

jQuery / AJAX – Legacy support and backend communication

Web Performance – Lighthouse, Core Web Vitals, PWA, caching strategies

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Build scalable, secure, and intelligent server-side systems:

C / C++ / Data Structures / Algorithms / OOPS

Java / J2EE / Spring / Spring Boot / Spring Cloud / Hibernate / Struts / Wicket

Microservices Architecture – API gateway, service registry, inter-service communication

Node.js / Express / NestJS – Modern JavaScript/TypeScript backend

REST & SOAP Web Services – API design, security, documentation (Swagger / Postman)

Python (Flask / FastAPI) – REST APIs, ML pipelines, automation

Shell Scripting (Linux/Unix) – Automation, cron jobs, log parsing, DevOps scripting

PHP / Laravel / CodeIgniter – Classic web backend development

Containerization & Orchestration: Docker, Kubernetes, Helm

CI/CD & Cloud: Jenkins, GitHub Actions, Azure DevOps Pipelines

☁️ Cloud & DevOps Mastery

Learn to build, deploy, and scale applications on the cloud:

AWS (EC2, S3, Lambda, DynamoDB, API Gateway, ECS)

Azure (App Services, Functions, CosmosDB, DevOps)

Google Cloud (GCP, Vertex AI, BigQuery, Cloud Run)

Monitoring & Logging: ELK Stack (Elasticsearch, Logstash, Kibana), Grafana, Prometheus

Infrastructure as Code (IaC): Terraform, AWS CDK, Azure Bicep

Version Control & Collaboration: Git, GitHub, GitLab, Bitbucket

CI/CD Pipelines: Build, test, deploy automation, rollback, release management

📱 App Development

Develop mobile and hybrid apps end-to-end:

Android (Java/Kotlin) – UI/UX, activity lifecycle, API integration

Hybrid Frameworks: Ionic, Cordova, React Native

Progressive Web Apps (PWA) – Offline-first, caching, mobile optimization

Firebase Integration: Auth, Firestore, Cloud Messaging

🤖 Artificial Intelligence & Machine Learning

Learn how modern AI systems are built and deployed:

AI Fundamentals: Neural networks, supervised/unsupervised learning

Machine Learning with Python: scikit-learn, TensorFlow, PyTorch

Natural Language Processing (NLP): Transformers, BERT, GPT

Computer Vision: OpenCV, YOLO, Image Classification

AI APIs & Integrations: Google DialogFlow, Azure Cognitive Services, OpenAI API

🧬 Generative AI, RAG & Agentic Systems

Special focus on real-world AI integration and automation:

Generative AI Models (GPT, Claude, Gemini, Llama, Mistral) – Practical implementation

Prompt Engineering – Designing powerful, reusable prompt frameworks

Retrieval-Augmented Generation (RAG) – Hybrid search + generation architectures

Agentic AI Systems – Building autonomous multi-agent workflows (e.g., AutoGPT, CrewAI)

Agentic RAG – Contextual memory, chaining, and reasoning systems

LangChain / LlamaIndex – RAG pipelines, document loaders, embeddings, vector DBs

Vector Databases: Pinecone, Chroma, Weaviate, FAISS

Knowledge Graphs & Context Management – Enterprise data linking with RAG

AI App Deployment: FastAPI + Streamlit + LangServe + Docker

Copilot & AI Tools: GitHub Copilot, ChatGPT API, Code Interpreter, Vertex AI Studio

Google AI Developer Kit (ADK) – Edge AI, TensorFlow Lite, Coral, and model serving

Voice AI & Conversational Design: Dialogflow CX, OpenAI Assistants, ElevenLabs

🔬 Data, Testing & Quality

Database Systems: MySQL, PostgreSQL, MongoDB, Oracle, DB2, Redis

Database Design: ERD, normalization, indexing, performance tuning

Testing Tools: JUnit, Mockito, Selenium, Cypress, Postman

TDD / BDD Practices: Unit, integration, and end-to-end testing

Logging & Monitoring: ELK, Splunk, Prometheus

Performance Optimization: Profiling, caching, concurrency

🧩 Operating Systems & Scripting

Windows / Linux / Ubuntu / Unix Administration

File Systems, Permissions, Networking, Process Management

Shell Scripting / Automation / Log Analysis

System Security and SSH Hardening

🧠 Bonus Topics

Mathematics for Programmers – Logic, combinatorics, probability, graph theory

Game Development Basics: Unity, Phaser.js, HTML5 Canvas

AI Ethics, Data Privacy, Responsible AI Design

Automation Projects & Web Crawling / Scraping: BeautifulSoup, Selenium, Puppeteer

No-Code / Low-Code Integrations: Zapier, Make, AI automations

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🐍 Python Programming – Learn by Doing
Course Overview
This class is designed for anyone who wants to learn Python from scratch or strengthen their coding skills. Whether you’re a complete beginner or looking to apply Python in data analysis, automation, or web development, this course will guide you step by step with practical examples and projects.

What You’ll Learn
✅ Python basics: variables, data types, operators, and control flow

✅ Functions and modules: writing reusable, clean code

✅ Working with files and data (CSV, JSON, text)

✅ Object-Oriented Programming (OOP) concepts

✅ Libraries for real-world tasks (e.g., pandas, matplotlib)

✅ Problem-solving strategies and debugging techniques

Teaching Style
Hands-on learning: You’ll write code in every session.

Project-driven: Build mini-projects like calculators, data visualizations, or simple web apps.

Adaptable pace: Lessons tailored to your level and goals (academic, professional, or hobby).

Who Is It For?
Students preparing for exams or computer science courses

Professionals wanting to automate tasks or analyze data

Curious learners who want to start coding as a hobby

Practical Details
📍 Online or in-person (depending on your location)

⏱ Flexible scheduling to fit your availability

🧑‍🏫 Personalized guidance with clear explanations and exercises