Data Engineering on AWS: build pipelines, lakehouses and streaming systems

From 36 £ /h

Learn how data actually moves through a modern company: ingestion, storage, transformation, orchestration and serving. I am a Lead Data and Machine Learning Engineer in Berlin with 9 years of building these systems at Amazon, Delivery Hero, Goldman Sachs and Orion S.A. This class teaches the same architecture and tooling I use at work.

WHO IT IS FOR

Analysts and backend developers moving into data engineering.
Data scientists who keep getting blocked by broken or missing pipelines.
Students and career switchers who want a portfolio project that looks like real production work.
Engineers preparing for data engineering interviews or AWS certifications.

WHAT WE COVER

SQL that holds up under pressure: joins, window functions, query plans and performance.
Data modelling: star schemas, slowly changing dimensions, and how to design tables people can actually query.
Python for data engineering: clean, testable transformation code.
Batch pipelines with Airflow and dbt, including testing and data quality checks.
Spark for large datasets, and when you genuinely do not need it.
Streaming with Kafka and Kinesis: events, ordering, exactly once, and the traps.
AWS in depth: S3, Glue, Redshift, Athena, Lambda and IAM, plus cost control.
Lakehouse patterns with Databricks and Delta or Iceberg.
Infrastructure as code with Terraform, and CI CD for data.
Monitoring, alerting and what to do at 3am when a pipeline fails.

HOW IT WORKS

We pick a realistic project in the first lesson, for example a pipeline that ingests raw events and serves a clean analytics table, and we build it over the following sessions. You write the code, I review it live and explain the trade offs. You finish with a repository you can show in an interview.

We can also work on your own company's problems if you bring them, as long as you can share enough of the shape of the data.

PRACTICAL DETAILS

Lessons are in English, online via webcam, and I work comfortably across time zones. You should already be able to write basic Python and SQL. If you are not there yet, start with my Python, SQL and Machine Learning class and we build up to this one.

Extra information

Message me first with your current level, what you want to build and any deadline. I will send back a short plan for the first lessons.

What you need: a laptop, a stable connection, Zoom or Google Meet, and Python installed. An AWS free tier account is useful from about the third lesson but is not needed to start. Basic Python and SQL are expected for this class.

I am based in Berlin (CET) and regularly teach students in other time zones, so ask if you need an early or late slot.

Location

Online from Germany

About Me

I am a Lead Data and Machine Learning Engineer based in Berlin, with over 9 years of building production data and AI systems at Amazon, Delivery Hero, Goldman Sachs and, currently, Orion S.A. I have been teaching on Apprentus since 2021 alongside that work, and I teach exactly what I do every day rather than theory I read about once.

My students are usually one of four people: a complete beginner who wants to learn programming properly from zero, a university or bootcamp student whose Python, SQL or machine learning assignment has stopped making sense, a working professional moving into data engineering, data science or AI, or a candidate preparing for technical interviews. I enjoy all four, and I adapt completely to which one you are.

How I teach: we start with a short conversation about where you are now and what you actually want to reach. I do not hand out a fixed syllabus before I know that. Every lesson is hands on. You write code while I watch, I review it live, and I explain the reasoning behind the fix instead of just giving you the fix. That is the part that makes it stick.

You finish each session with something concrete: a working script, a clean notebook, a pipeline that runs, or an answer you could confidently give in an interview. Between lessons you get exercises and a project that grows week by week, so after a few months you have something real to show an employer.

I am patient with beginners who are starting from nothing, and direct with people who want to be pushed hard. If something you are doing would not survive in a real production system, I will say so, because that honesty is the reason to learn from a practitioner instead of a video course.

Lessons are in English, online via webcam, and I am used to working across time zones. My open source guide for machine learning interviews has more than 700 stars on GitHub, and I use the same material with students preparing for interviews.

Education

MSc in Computer Science, Concordia University Ann Arbor, United States (2021 to 2023), with a focus on machine learning and data systems.

BSc in Computer Science, Government College University Lahore, Pakistan (2013 to 2017), covering algorithms, databases and software engineering.

I also keep learning continuously through AWS, Google Cloud, Databricks and Terraform certification tracks.

Experience / Qualifications

WORK EXPERIENCE (9+ years)
Lead Data and Machine Learning Engineer, Orion S.A., Berlin (2024 to present)
Senior Data Engineer, Delivery Hero, Berlin
Senior Data Engineer, Amazon
Data Engineering consultant (contract), Goldman Sachs, London (2021)
Earlier roles at NorthBay Solutions (AWS Advanced Consulting Partner) and Teradata

WHAT I WORK WITH DAILY
Python, SQL, Spark, Kafka, Airflow, dbt, Databricks, Terraform
AWS (SageMaker, Bedrock, Glue, Redshift, S3), Google Cloud and BigQuery
Machine learning, deep learning, natural language processing
Generative AI: RAG, LangChain, vector databases, OpenAI and AWS Bedrock

CERTIFICATIONS
AWS Certified Machine Learning Specialty
AWS Certified Data Engineer Associate
AWS Certified Solutions Architect Associate
AWS Certified Developer Associate
AWS Certified Cloud Practitioner
Google Cloud certified
HashiCorp Terraform Associate
Databricks certified
Deep Learning, Machine Learning and Statistics specializations

OPEN SOURCE
My machine learning interview guide on GitHub has more than 700 stars and is used by candidates preparing for data and ML interviews.

TEACHING
Teaching on Apprentus since April 2021.

Age

Adults (18-64 years old)

Student level

Intermediate

Advanced

Duration

60 minutes

The class is taught in

English

Urdu

Panjabi

Pashto

Skills

Database

Python

Computer programming

Availability of a typical week

(GMT -04:00)

New York

Online via webcam

Mon

Tue

Wed

Thu

Fri

Sat

Sun

00-04

04-08

08-12

12-16

16-20

20-24

Python, SQL and Machine Learning with a Lead Data & AI Engineer (ex Amazon)

34 £ /h

Learn Python, SQL, machine learning and AI from someone who builds these systems in production every day. I am a Lead Data and Machine Learning Engineer based in Berlin, with 9 years at Amazon, Delivery Hero, Goldman Sachs and now Orion S.A., and I have been teaching here since 2021.

WHO THIS CLASS IS FOR

Complete beginners who want to learn programming properly, from zero, with no assumptions.
University and bootcamp students stuck on Python, SQL, algorithms or a machine learning assignment.
Working professionals moving into data engineering, data science or AI roles.
Candidates preparing for technical interviews at product and tech companies.

WHAT WE CAN COVER

We pick the path together based on your goal. Options include:

Python fundamentals, clean code and object oriented programming
Data structures and algorithms, with the reasoning behind each choice
SQL and databases, from joins and window functions to designing a warehouse
Pandas, NumPy, data cleaning and exploratory analysis
Machine learning: regression, classification, trees, model evaluation, and the quiet mistakes that ruin a model
Deep learning and natural language processing foundations
Generative AI in practice: RAG, embeddings, vector databases, LangChain, OpenAI and AWS Bedrock
Data engineering on AWS: S3, Glue, Redshift, SageMaker, Airflow, Spark and dbt
Interview preparation, including mock interviews and system design for data roles

HOW LESSONS WORK

In the first lesson we work out where you are and what you actually want to reach, and I map a path to it. After that every session is hands on. You write code, I review it live, and I explain the reasoning rather than just handing you the answer.

You finish each lesson with something that works: a script, a notebook, a query, a pipeline, or an answer you could confidently give in an interview. Between lessons you get exercises and a project that grows week by week, so you end up with something real to show an employer.

WHY LEARN WITH ME

I teach what I do. The examples come from real systems that serve real users, not from textbook datasets. I will also tell you honestly when an approach will not hold up in production, which is the main reason to learn from a practitioner rather than a video course.

My open source guide for machine learning interviews has more than 700 stars on GitHub and is used by candidates preparing for data and ML roles.

PRACTICAL DETAILS

Lessons are in English, online via webcam, and I am comfortable working across time zones. Suitable for teenagers from 14 and for adults. No prior experience is needed for the beginner track.

Machine Learning and Generative AI in practice: from first model to RAG systems

36 £ /h

This class is for people who already write some Python and now want to build machine learning and generative AI systems that work outside a notebook. I am a Lead Data and Machine Learning Engineer in Berlin with 9 years at Amazon, Delivery Hero, Goldman Sachs and Orion S.A., and I teach the same methods I use at work.

WHO IT IS FOR

Developers and analysts moving into machine learning or AI roles.
Students who understand the theory but have never shipped a model.
Founders and product people who want to build a real AI feature rather than a demo.
Anyone preparing for machine learning or AI engineering interviews.

WHAT WE COVER

Framing a problem: what is predictable, what is not, and how to tell before you waste a month.
Core machine learning: regression, classification, tree based models, feature engineering.
Model evaluation done properly: leakage, class imbalance, baselines, and why your accuracy score is lying to you.
Deep learning and natural language processing foundations.
Large language models in practice: prompting, structured output, evaluation and cost control.
Retrieval augmented generation end to end: chunking, embeddings, vector databases, reranking, and measuring whether the answers are actually correct.
Agents and tool use with LangChain and LangGraph.
Deployment: turning a model or an AI feature into a service, plus monitoring and drift.

HOW IT WORKS

We agree on a target project in the first lesson and build towards it. You write the code, I review it live and explain the reasoning. You leave with a working system in your own repository rather than a folder of tutorials.

I will tell you honestly when an approach will not survive real traffic or real data. That is the main reason to learn this from someone who runs it in production.

PRACTICAL DETAILS

Lessons are in English, online via webcam, and I work comfortably across time zones. You need working Python basics for this class. If you are starting from zero, book my Python, SQL and Machine Learning class instead and we build up to this one.

4.85

(13)

Engineer and senior professor of engineering sciences provides support courses in analog and digital electronics at all levels, engineering schools. having a scientific and technical knowledge, five years of experience in the field of teaching, teaching and a sense of listening and analysis, I am able to help pupils and students and train them in the chapters of which they have difficulties. for more info please contact me

Matías

4.85

(13)

Python is one of the best, if not the best, language to start learning programming. It is also one of the most widely used languages today, especially in cutting-edge areas such as machine learning.

This popularity means that Python is constantly evolving. It offers a wide range of tools and libraries, which are free and very varied.

As an aeronautical engineer, I like to share my knowledge and derive satisfaction from it by teaching and motivating others.

I'm used to working with people of different ages. I believe in the importance of segmenting learning, visualizing progress, setting concrete goals and practicing regularly.

Beyond these general principles, there is no magic rule or method. Some approaches work with some students but not with others. Adaptation to individual needs is therefore the main objective of private lessons. So I will do my best to find what motivates and helps my student.

Adam

4.85

(13)

Learn to code with method and logic
Whether it's to succeed in the NSI (Digital Sciences and Technology) specialization in high school, design personal projects, or prepare for higher scientific studies, mastering code relies on solid algorithmic thinking. I help students understand the structure of programming languages and the logic of data.

Subject areas and languages taught:

Algorithms & Logic: Designing data structures and solving problems.

Programming Languages: Python, C/C++, C# and Java.

Data Management: Analysis and SQL queries / databases.

Basic Web Development: HTML & CSS for creating structured pages.

The goal is to take the student from simply writing code to true autonomy in development.

Amin

4.85

(13)

Python is the most in-demand programming language in the world right now — and one of the easiest to learn with the right guidance.
Whether you've never written a line of code or you're a student who needs to pass a programming course, this is a practical, no-fluff introduction that gets you writing real code from session one.
What we can cover depending on your goals:

Python fundamentals: variables, loops, functions, data structures
- Object-oriented programming (OOP)
- Data manipulation with pandas and NumPy
- Introduction to machine learning with scikit-learn
- Database management with SQL
- C and Java upon request
- MATLAB and R available for engineering/science students

Why learn with me?
I'm not a student teaching on the side — I'm a professional engineer who uses Python daily for data analysis, modeling, and automation. I know exactly which concepts matter in the real world and which ones you can skip for now.
Sessions are 100% personalized: I adapt the pace, the examples, and the exercises to your background and your goal — whether that's passing your university exam, building a project, or landing a job.

Gaëlle

4.85

(13)

While adults are still debating whether kids should use AI, they are already using it.
The question isn't "should they?" it's "how do we do it intelligently?"

In this course, your child will discover:
✓ What AI actually is: not magic, not mystery. How machines think, what they can do, what they can't
✓ How ChatGPT really works: not just "ask a question and get an answer," but why it responds that way, where it fails, when to trust it
✓ What LLMs are (Large Language Models): in language they understand, not tech jargon
✓ Create with AI: custom avatars, interactive stories, real projects using real tools
✓ Think critically about AI: Bias, privacy, creativity. What does AI do better than humans? What can't it do?
✓ Real-world applications: How AI transforms medicine, education, art, gaming, everyday life

Why this is different:
Most AI courses for kids teach "here's the tool, use it." I teach how to think about AI.
Your child will learn to see AI not as black magic or a solution to everything, but as a powerful tool with real limits.
And, more importantly: that they can control how they use it.

What they take home:
Real projects they created (custom avatar, interactive app, analysis of a real AI case study). A genuine understanding of how it works. And the ability to use AI responsibly and creatively.

Format: Online | 60–90 min sessions | Flexible, adapted to their age and pace

For curious kids asking "How does ChatGPT actually know things?"

Giuliano

4.85

(13)

Python is a powerful and versatile programming language with countless possibilities. You can use it for data analysis, image processing, automation, software development, hardware control, and much more.

Do you want to create your own software?
Work with data or images?
Automate repetitive tasks?
Control or manage your own hardware?

Whether you are just starting to learn Python or already have a specific project and need some guidance, I would be happy to help you.

My goal is to explain things clearly, adapt to your level, and help you understand not only how to make something work, but also why it works.

Let's turn your ideas into working Python projects!

Salah

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(13)

Master Python with Personalized Courses

Discover the art of programming with Python courses tailor-made to meet your specific needs. Whether you are a beginner, intermediate or professional, my lessons are suitable for all levels.

Why Choose My Courses?

Personalized Teaching Approach: Each course is tailored to your skill level and individual goals.

Practical Experience: Learn by doing with real-world projects that build your understanding and skills.

Ongoing Support: Get unlimited email support for any questions you have between sessions.

As a Python expert, I have a passion for teaching and sharing my knowledge. My goal is to guide you effectively in your learning journey.

Book Your First Lesson:

Start your journey to Python mastery now by booking your first lesson. Whether you aspire to enter the development field or hone your existing skills, these courses are designed for you.

Mohamed

4.85

(13)

In this course, you will learn how to efficiently package, containerize, and deploy Python applications and microservices using Docker. The course covers fundamental Docker concepts, best practices for structuring Python projects, and strategies for building scalable and portable applications. Through hands-on projects, you will gain practical experience in creating Docker images, managing containers, and orchestrating microservices, enabling seamless deployment across different environments.

Contact me if you want to have more information about the course!

Hayat

4.85

(13)

This course is designed for anyone interested in learning data science using Python. It provides a hands-on introduction to fundamental data analysis tools such as NumPy, pandas, matplotlib, and seaborn. You'll learn how to manipulate datasets, create visualizations, and lay the foundations for statistical analysis and machine learning.

The course combines theory and practical exercises for effective, practical progress. No prior programming experience is necessary: we'll start with the basics to build solid, usable skills quickly.

Amr

4.85

(13)

# **Master C/C++: Build the Foundation of Modern Software Development**

Unlock the power of one of the most influential programming languages in computing history! Whether you're an absolute beginner or looking to deepen your expertise, this comprehensive C/C++ course delivers structured learning from fundamentals to advanced concepts that power operating systems, game engines, and high-performance applications.

## **Why Choose This C/C++ Program?**

**Industry-Relevant Curriculum:** Learn expert guidance on the design of effective classes, functions, templates, and inheritance patterns that form the backbone of professional C++ development. Move beyond basic syntax to understand how to write clean, efficient, and maintainable code that stands the test of time.

**Templates & Generic Programming Mastery:** Go beyond introductory material with in-depth coverage of templates—the cornerstone of modern C++—enabling you to create robust, reusable code components that work across multiple data types. Discover how function templates, class templates, and variadic templates work to maximize your coding efficiency.

**Practical, Hands-On Approach:** This isn't just theory! You'll build real-world projects that demonstrate memory management, object-oriented programming, and system-level programming techniques used in today's technology landscape.

## **Your Learning Journey**

Our structured path takes you from writing your first "Hello World" program through advanced template metaprogramming, with special attention to modern C++ standards (up to C++20). You'll gain the confidence to tackle complex programming challenges and understand the "why" behind effective C++ practices—not just the "how."

## **Transform Your Career Today**

C/C++ skills remain in high demand across industries from finance to gaming to IoT. By mastering these foundational languages, you'll develop problem-solving abilities that translate to any programming environment.

Ali

4.85

(13)

I teach machine learning, AI and Python online to university students, postgraduates, career changers and serious beginners across the UK and Europe. Lessons are in English.

I hold an MSc in Electronics and Electrical Engineering with Distinction and I teach as a Visiting Lecturer on a Master's level module covering data analytics, machine learning and generative AI at a UK university. I also have two accepted international conference papers on deep learning for image classification. I set and mark postgraduate assignments myself, so I know where marks are won and lost on this kind of work.

Who this is for

Undergraduates and postgraduates on AI, ML, data science or computer science modules at any European university. Final year, Master's and thesis students working on a machine learning project. IB and A Level students moving into computing or engineering. Professionals retraining for data roles. Complete beginners who want to learn Python properly rather than copying it from videos.

I work with students on UK, IB and continental European programmes. I have tutored engineering students in Germany and international school students across several countries, so an unfamiliar syllabus or a module taught in a different structure is not a problem. Send me the material and I will work from it.

What we cover

Python for data science with NumPy, Pandas, Matplotlib and scikit-learn. Deep learning using TensorFlow and Keras. Core theory including regression, classification, clustering, decision trees, random forests, neural networks and CNNs, together with the linear algebra, calculus and statistics underneath them. Computer vision and image classification, which is my published research area. Model evaluation, overfitting and hyperparameter tuning. Writing machine learning work up to academic standard, covering methodology, results and critical evaluation.

How lessons work

Send me your module handbook, assignment brief, thesis spec or the code that will not run, and I plan the session around it before we meet. Nothing generic.

In the lesson I explain the concept with a worked example, then you take the keyboard while I watch and correct, because you learn far more doing it than watching me do it. You finish with annotated notes and a clear next step, and you can message me between sessions with questions.

Practical details

Online over Google Meet or Zoom with screen sharing and a shared whiteboard. Sessions run 60 or 90 minutes. I am based in the UK and teach across GMT and Central European time, with evening and weekend slots that suit students anywhere in Europe.

Tell me your course, your deadline and exactly where you are stuck, and I will come back with a plan for the first session.

Baia

4.85

(13)

I'm a working MEP engineer, currently building Python automation for Revit workflows daily - plan checks, model coordination, and repetitive drafting tasks. I teach other engineers, architects, and BIM professionals how to do the same, using pyRevit and real project workflows, not toy examples.

Topics include:
pyRevit fundamentals and setup
Automating repetitive Revit tasks (model checks, plan generation, data extraction)
Writing custom scripts for your firm's specific workflows
Applying Python automation to real MEP/BIM projects

Jayaram

4.85

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Overview

Transitioning from learning data science theory to solving actual business problems is the hardest step for any aspiring data professional. [Insert Chosen Course Title] is an intensive, mentor-led program designed to simulate a real-world data team environment. Instead of working through synthetic, pre-cleaned textbook datasets, you will take on messy, complex industry scenarios and turn them into end-to-end data products.

What You’ll Experience

End-to-End Execution: Walk through the full data lifecycle—from problem scoping and data extraction to exploratory analysis, modeling, and executive stakeholder presentation.

Industry-Standard Workflows: Work with messy real-world datasets, practice Git-based version control, write production-ready code, and structure reports that business leaders actually care about.

1-on-1 & Group Mentorship: Receive continuous code reviews, architectural feedback, and project guidance mirroring the experience of working under a Senior Data Scientist or Analytics Lead.

Portfolio-Ready Deliverables: Graduate with 2–3 complete, polished projects that demonstrate actual business value to hiring managers—not just another churn prediction copy-pasted from Kaggle.

Who This Is For
Aspiring Data Analysts, Data Scientists, and recent graduates who know Python, but want the practical experience, confidence, and portfolio needed to land high-impact roles in the industry.

Anatole

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A patient and passionate instructor offers a customized learning path in Java, JavaScript, or Python. The goal of this course is to enable you to develop strong algorithmic thinking skills, regardless of your starting level. Throughout the course, active listening and patience are emphasized to ensure that no question goes unanswered. The sessions are highly interactive, and the problem is broken down step by step.

Neha

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Learn how to build modern websites and mobile applications from scratch and develop the practical skills needed for real-world projects.

In this Frontend & Mobile Development course, I’ll guide you step by step through the technologies and tools commonly used by developers, including HTML, CSS, JavaScript, Angular, Git, GitHub, VS Code, and mobile application development.

You’ll learn how to create responsive and interactive websites, build structured applications with Angular, manage your code using Git and GitHub, and use VS Code efficiently for development. We’ll also explore how frontend technologies can be used to create mobile applications.

The course is suitable for beginners and intermediate learners. Lessons are practical and project-based, so you’ll learn by actually building websites and applications rather than only studying theory.

My goal is to help you understand how and why the code works, improve your problem-solving skills, learn professional development practices, and gain the confidence to create your own projects independently.

Lessons can be adapted to your experience level, learning pace, and personal or career goals.