Write your awesome label here.

🎓 Certification Included 🎓 

Upon completion of project material

Prerequisites:

🤩 Even if you lack experience in any of the areas below, this project provides the necessary tools and resources to learn and fill the gap.

  • Python and Pandas programming skills: Basic to intermediate knowledge of Python and familiarity with the Pandas library for data manipulation.

  • SQL and relational databases: Basic familiarity with SQL and how relational databases work will help you understand data storage and querying processes.

  • Google Cloud Platform account: Set up a free trial on Google Cloud Platform (GCP) to access various services used in the project.

  • Ready to learn: No matter your current skill level, this project is designed to help you succeed. Come eager to learn and ready to tackle new challenges!

⏰ Estimated Completion Time:

  • For Beginners (1+ year of programming experience with Python): 1-2 weeks.                 

  • For Experienced Data/Software Professionals (1+ years of professional experience with Python or having a CS degree): 1-3 days.

Data & Cloud Engineering Project

Build an End-to-End Data Pipeline on Google Cloud Platform

Data & Cloud Engineering Project #1

Build a modern data pipeline on Google Cloud Platform from scratch. This project will provide you with the skills to automate the extraction, transformation, and storage of data using advanced Cloud technologies.
Write your awesome label here.

What you will learn:

Build a modern data pipeline on Google Cloud Platform from scratch. This project will provide you with the skills to automate the extraction, transformation, and storage of data using advanced Cloud technologies.

🎯 Professionals typically need at least three months to acquire the skills that this project can teach you in less than two weeks!

What you will learn:

  • Extract data from public APIs: Utilise Python to fetch data from public APIs, which is crucial for many data-driven applications.
  • Transform data with Python: Utilize libraries like Pandas to clean and structure raw data, preparing it for storage and analysis.
  • Deploy and manage Data Pipeline: Deploy your data pipeline using Google Cloud services such as Cloud Storage, Cloud Functions, and BigQuery.
  • Automate data workflows: Leverage Cloud Scheduler to automate the daily execution of your data pipeline.
  • Create Interactive Visualizations: Use Looker Studio to create dynamic dashboards that visually represent your data insights.
  • Prepare for interviews: Gain valuable insights on presenting this project to potential employers effectively and handling common interview questions 

Key Performance Metrics:

🔥 Completion Rate: 88.2% (15 out of 17 participants of all levels who started this project managed to complete it).
⭐ Rating: 5/5 (15 Reviews. Check below for details).
  • Extract data from public APIs: Utilise Python to fetch data from public APIs, which is crucial for many data-driven applications.
  • Transform data with Python: Utilize libraries like Pandas to clean and structure raw data, preparing it for storage and analysis.
  • Deploy and manage Data Pipeline: Deploy your data pipeline using Google Cloud services such as Cloud Storage, Cloud Functions, and BigQuery.
  • Automate data workflows: Leverage Cloud Scheduler to automate the daily execution of your data pipeline.
  • Create Interactive Visualizations: Use Looker Studio to create dynamic dashboards that visually represent your data insights.
  • Prepare for interviews: Gain valuable insights on presenting this project to potential employers effectively and handling common interview questions 

Prerequisites:

  • Python and Pandas programming skills: Basic to intermediate knowledge of Python and familiarity with the Pandas library for data manipulation.

  • Google Cloud Platform account: Set up a free trial on Google Cloud Platform (GCP) to access various services used in the project.

  • SQL and relational databases: Basic familiarity with SQL and how relational databases work will help you understand data storage and querying processes.

🤩 Even if you lack experience in any of the above areas, this project provides the necessary resources to learn and fill the gap.

🎓 Certification Included 🎓 

Upon completion of project material

Data & Cloud Engineering Project

Build an End-to-End Data Pipeline on Google Cloud Platform

Build a modern data pipeline on Google Cloud Platform from scratch. This project will provide you with the skills to automate the extraction, transformation, and storage of data using advanced Cloud technologies.

🎯 Professionals typically need at least three months to acquire the skills that this project can teach you in less than two weeks!
Write your awesome label here.

What you will learn:

  • Extract data from public APIs: Utilise Python to fetch data from public APIs, which is crucial for many data-driven applications.
  • Transform data with Python: Utilize libraries like Pandas to clean and structure raw data, preparing it for storage and analysis.
  • Deploy and manage Data Pipeline: Deploy your data pipeline using Google Cloud services such as Cloud Storage, Cloud Functions, and BigQuery.
  • Automate data workflows: Leverage Cloud Scheduler to automate the daily execution of your data pipeline.
  • Create Interactive Visualizations: Use Looker Studio to create dynamic dashboards that visually represent your data insights.
  • Prepare for interviews: Gain valuable insights on presenting this project to potential employers effectively and handling common interview questions.

Prerequisites:

🤩 Even if you lack experience in any of the below areas, this project provides the necessary resources to learn and fill the gap.

  • Python and Pandas programming skills: Basic to intermediate knowledge of Python and familiarity with the Pandas library for data manipulation.

  • SQL and relational databases: Basic familiarity with SQL and how relational databases work will help you understand data storage and querying processes.

  • Google Cloud Platform account: Set up a free trial on Google Cloud Platform (GCP) to access various services used in the project.

  • Ready to learn: No matter your current skill level, this project is designed to help you succeed. Come eager to learn and ready to tackle new challenges!

⏰ Estimated Completion Time:

  • For Beginners (6+ months into programming): 1-2 weeks.          

  • For Experienced Data/Software Professionals (1+ years of professional experience with Python): 1-3 days.

Key Performance Metrics:

🔥 Completion Rate: 88.2% (15 out of 17 participants of all levels who started this project managed to complete it).
⭐ Rating: 5/5 (15 Reviews. Check below for details).

🎓 Certification Included 🎓 

Upon completion of project material

Data & Cloud Engineering Project

Build an End-to-End Data Pipeline on Google Cloud Platform

Build a modern data pipeline on Google Cloud Platform from scratch. This project will provide you with the skills to automate the extraction, transformation, and storage of data using advanced Cloud technologies.

🎯 Professionals typically need at least three months to acquire the skills that this project can teach you in less than two weeks!

Write your awesome label here.

What you will learn:

  • Extract data from public APIs: Utilise Python to fetch data from public APIs, which is crucial for many data-driven applications.

  • Transform data with Python: Utilize libraries like Pandas to clean and structure raw data, preparing it for storage and analysis.

  • Deploy and manage Data Pipeline: Deploy your data pipeline using Google Cloud services such as Cloud Storage, Cloud Functions, and BigQuery.

  • Automate data workflows: Leverage Cloud Scheduler to automate the daily execution of your data pipeline.

  • Create Interactive Visualizations: Use Looker Studio to create dynamic dashboards that visually represent your data insights.

  • Prepare for interviews: Gain valuable insights on presenting this project to potential employers effectively and handling common interview questions 

Prerequisites:

🤩 Even if you lack experience in any of the below areas, this project provides the necessary resources to learn and fill the gap.

  • Python and Pandas programming skills: Basic to intermediate knowledge of Python and familiarity with the Pandas library for data manipulation.

  • SQL and relational databases: Basic familiarity with SQL and how relational databases work will help you understand data storage and querying processes.

  • Ready to learn: No matter your current skill level, this project is designed to help you succeed. Come eager to learn and ready to tackle new challenges!

  • Google Cloud Platform account: Set up a free trial on Google Cloud Platform (GCP) to access various services used in the project.

⏰ Estimated Completion Time:

  • For Beginners (6+ months into programming): 1-2 weeks.                                                     

  • For Experienced Data/Software Professionals (1+ years of professional experience with Python): 1-3 days.

Key Performance Metrics:

🔥 Completion Rate: 88.2% (15 out of 17 participants of all levels who started this project managed to complete it).
⭐ Rating: 5/5 (15 Reviews. Check below for details).

🎓 Certification Included 🎓 

Upon completion of project material


Data & Cloud Engineering Project

Build an End-to-End Data Pipeline on Google Cloud Platform

Build a modern data pipeline on Google Cloud Platform from scratch. This project will provide you with the skills to automate the extraction, transformation, and storage of data using advanced Cloud technologies.

🎯 Professionals need at least three months to acquire the skills that this project can teach you in less than two weeks!

Write your awesome label here.

What you will learn:

  • Extract data from public APIs: Utilise Python to fetch data from public APIs, which is crucial for many data-driven applications.

  • Transform data with Python: Utilize libraries like Pandas to clean and structure raw data, preparing it for storage and analysis.

  • Deploy and manage Data Pipeline: Deploy your data pipeline using Google Cloud services such as Cloud Storage, Cloud Functions, and BigQuery.

  • Automate data workflows: Leverage Cloud Scheduler to automate the daily execution of your data pipeline.

  • Create Interactive Visualizations: Use Looker Studio to create dynamic dashboards that visually represent your data insights.

  • Prepare for interviews: Gain valuable insights on presenting this project to potential employers effectively and handling common interview questions 

Prerequisites:

🤩 Even if you lack experience in any of the below areas, this project provides the necessary resources to learn and fill the gap.

  • Python and Pandas programming skills: Basic to intermediate knowledge of Python and familiarity with the Pandas library for data manipulation.

  • SQL and relational databases: Basic familiarity with SQL and how relational databases work will help you understand data storage and querying processes.

  • Ready to learn: No matter your current skill level, this project is designed to help you succeed. Come eager to learn and ready to tackle new challenges!

  • Google Cloud Platform account: Set up a free trial on Google Cloud Platform (GCP) to access various services used in the project.

⏰   Estimated Completion Time:

  • For Beginners (6+ months into programming): 1-2 weeks.                                                  

  • For Experienced Data/Software Professionals (1+ years of professional experience with Python): 1-3 days.

Key Performance Metrics:

🔥Completion Rate: 88.2% (15 out of 17 participants of all levels who started this project managed to complete it).
⭐ Rating: 5/5 (15 Reviews. Check below for details).

🎓 Certification Included 🎓 

Upon completion of project material

💭 Who is this project for?

This project is perfect for many tech professionals, from beginners to experienced engineers looking to explore data and cloud technologies. Whether you're looking to add impressive projects to your portfolio or starting your first project in the cloud, this project is designed just for you:

#1 Aspiring 
Data Engineers & Python Developers

If you're starting your tech career or enhancing your programming skills, this project offers a standout opportunity. Most beginners don't know how to deploy end-to-end data pipeplines in a production environment. By building and managing a production-grade data pipelines on Google Cloud, you'll distinguish yourself from other candidates. This practical, scalable project experience can help you land your first full-time job.

#2 Machine Learning and Software Engineers

For Machine Learning and Software Engineers, this project is an excellent chance to expand your expertise into data collection and cloud infrastructure management. It's perfect for professionals eager to learn about data pipelines for machine learning models or those interested in automating web data interactions. This knowledge is crucial for integrating robust data handling into your development processes.

#3 Experienced Cloud and BI Engineers

If you're proficient in cloud technologies or business intelligence, this project will broaden your capabilities by introducing advanced data processing and automation in Google Cloud. Learning to implement data pipelines and task scheduling with Cloud Functions and Cloud Scheduler will enhance your role and pave the way for new career prospects.

#4 Career Switchers to Tech

If you're transitioning into tech from fields like finance, marketing, or science, this project is your gateway. It offers hands-on experience with coding, data handling, and cloud deployment, equipping you with the skills needed for tech roles. This project ensures you gain the confidence to tackle technical tasks and discussions, positioning you well for roles in data and cloud engineering.

💭 Who is this project for?

This project is perfect for many tech professionals, from beginners to experienced engineers looking to explore data and cloud technologies. Whether you're looking to add impressive projects to your portfolio or starting your first project in the cloud, this project is designed just for you:

#1 Aspiring 
Data Engineers & Python Developers

If you're starting your tech career or enhancing your programming skills, this project offers a standout opportunity. Most beginners don't know how to deploy end-to-end data pipeplines in a production environment. By building and managing a production-grade data pipelines on Google Cloud, you'll distinguish yourself from other candidates. This practical, scalable project experience can help you land your first full-time job.

#2 Machine Learning and Software Engineers

For Machine Learning and Software Engineers, this project is an excellent chance to expand your expertise into data collection and cloud infrastructure management. It's perfect for professionals eager to learn about data pipelines for machine learning models or those interested in automating web data interactions. This knowledge is crucial for integrating robust data handling into your development processes.

#3 Experienced Cloud and BI Engineers

If you're proficient in cloud technologies or business intelligence, this project will broaden your capabilities by introducing advanced data processing and automation in Google Cloud. Learning to implement automated data pipelines and task scheduling with Cloud Functions and Cloud Scheduler will enhance your role and pave the way for new career prospects.

#4 Career Switchers to Tech

If you're transitioning into tech from fields like finance, marketing, or science, this project is your gateway. It offers hands-on experience with coding, data handling, and cloud deployment, equipping you with the skills needed for tech roles. This project ensures you gain the confidence to tackle technical tasks and discussions, positioning you well for roles in data and cloud engineering.

 What's included? 

This is not just a project; it's a complete package that contains everything you need to build the project successfully and master the given skills and technologies. Specifically, it offers:

💎 Real-World Portfolio Project:

"Build an End-to-End Data Pipeline on Google Cloud Platform"

We provide detailed, step-by-step instructions on how to start, build, and deploy your project from scratch. You don't need to worry about a thing. Every step of the process is clearly documented in an easy-to-read format. We provide both code and instructions because we want you to concentrate on the project's core value: "Learning how to combine cloud technologies to build a high-value system that can gather data from any API"!

By implementing this project, you'll gain experience in high-demand cloud technologies and skills while learning how to build a production-ready project. You'll be able to add a unique portfolio project to your resume, setting you apart from other candidates and boosting your confidence for your interviews to secure your next high-paying job in data!

🌟 By the end of the project, you will have developed and deployed an automated Batch Data Pipeline on Google Cloud Platform to gather weather data daily from Weather API using modern cloud-based technologies.


🎁 Bonuses Included with Every Enrollment:

We offer much more than just a project. You'll engage with various technologies and tools, and to help you navigate them, we provide tailored mini-courses. These courses cover a range of essential topics, from Python and Google Cloud fundamentals to setting up a free Google Cloud Account and using Data Lakes such as Cloud Storage and Data Warehouses such as BigQuery. Everything you need to know is included.

Furthermore, we offer mini-courses on Git and GitHub, complete with detailed instructions on creating a GitHub repository and uploading your code. This visibility can attract recruiters and companies.

We also guide you in sharing your project on LinkedIn to secure your next interviews. Our support extends to offering advice on presenting the project in interviews and responding to common interview questions.

Finally, you'll receive access to our active community of 40+ individuals working on similar projects. Here, you can ask questions, get answers, and receive support from other members and the instructor. We pride ourselves on our excellent community support, as noted by our users.      

😍 Detailed Description of Your Bonuses:
1. 👨‍💻 Best free resources to learn Python and Pandas if you’re not familiar already
2. ⚙️ Local Environment Setup: How to install Python, VSCode and Anaconda (if you haven’t done already)
3. 📚Mini-Courses & extra lessons to cover the following:
         - API Fundamentals
         - Introduction Google Cloud Platform
         - How to Set Up Your Google Cloud Platform Free Trial Account
         - Security and Access Permissions On Google Cloud Platform
         - Cloud Storage and Data Lake Fundamentals
         - BigQuery and Data Warehousing Fundamentals
         - Cloud Functions Fundamentals
         - Introduction to Git & GitHub
4. 📂 Instructions and well-structured readme file to deploy your project on Github
5. 🌐 Networking Guidelines to share your Project on LinkedIn and attract recruiters
6. 👔 Interview Preparation with common interview question on your project
7. 📝 Final Assesment to test your acquired knowledge
8. 🏅Certificate of completion to share with your network
9. 🌍 Access to our Slack Community 🌍 where we communicate daily to help each other on the projects and job searching
😊 Don't miss this offer!

 What's included? 

This is not just a project; it's a complete package that contains everything you need to build the project successfully and master the given skills and technologies. Specifically, it offers:

💎 Real-World Portfolio Project:

"Build an End-to-End Data Pipeline on Google Cloud Platform"


We provide detailed, step-by-step instructions on how to start, build, and deploy your project from scratch. You don't need to worry about a thing. Every step of the process is clearly documented in an easy-to-read format. We provide both code and instructions because we want you to concentrate on the project's core value: "Learning how to combine cloud technologies to build a high-value system that can gather data from any API"!

By implementing this project, you'll gain experience in high-demand cloud technologies and skills while learning how to build a production-ready project. You'll be able to add a unique portfolio project to your resume, setting you apart from other candidates and boosting your confidence for your interviews to secure your next high-paying job in data!

🌟 By the end of the project, you will have developed and deployed an automated Batch Data Pipeline on Google Cloud Platform to gather weather data daily from Weather API using modern cloud-based technologies.

🎁 Bonuses Included with Every Enrollment:

We offer much more than just a project. You'll engage with various technologies and tools, and to help you navigate them, we provide tailored mini-courses. These courses cover a range of essential topics, from Python and Google Cloud fundamentals to setting up a free Google Cloud Account and using Data Lakes such as Cloud Storage and Data Warehouses such as BigQuery. Everything you need to know is included.

Furthermore, we offer mini-courses on Git and GitHub, complete with detailed instructions on creating a GitHub repository and uploading your code. This visibility can attract recruiters and companies.

We also guide you in sharing your project on LinkedIn to secure your next interviews. Our support extends to offering advice on presenting the project in interviews and responding to common interview questions.

Finally, you'll receive access to our active community of 40+ individuals working on similar projects. Here, you can ask questions, get answers, and receive support from other members and the instructor. We pride ourselves on our excellent community support, as noted by our users.      

😍 Detailed Description of Your Bonuses:
1. 👨‍💻 Best free resources to learn Python and Pandas if you’re not familiar already
2. ⚙️ Local Environment Setup: How to install Python, VSCode and Anaconda (if you haven’t done already)
3. 📚Mini-Courses & extra lessons to cover the following:
- API Fundamentals
- Introduction Google Cloud Platform
- How to Set Up Your Google Cloud Platform Free Trial Account
- Security and Access Permissions On Google Cloud Platform- Cloud Storage and Data Lake Fundamentals
- BigQuery and Data Warehousing Fundamentals
- Cloud Functions Fundamentals
- Introduction to Git & GitHub
4. 📂 Instructions and well-structured readme file to deploy your project on Github
5. 🌐 Networking Guidelines to share your Project on LinkedIn and attract recruiters
6. 👔 Interview Preparation with common interview question on your project
7. 📝 Final Assesment to test your acquired knowledge
8. 🏅Certificate of completion to share with your network
9. 🌍 Access to our Slack Community 🌍 where we communicate daily to help each other on the projects and job searching
😊 Don't miss this offer!

What Our Students Say ❤️

What Our Students Say ❤️

WHAT YOU ARE GOING TO BUILD

Project architecture diagram:

   Project Workflow 

Here is the outline of the process you will follow to complete the project:

   Project workflow:

   Project workflow:

1. Getting Started:
Define the project, establish requirements, and devise an implementation strategy. Learn the essential steps for setting up and starting the project.

2. Mini-Course: API Fundamentals
Learn API fundamentals, what is an API, how data professionals uses APIs, how to get access and make API calls to extract data using Python and Postman.

3. Account Setup: Create an OpenWeather Account
Create a Free OpenWeather Account to get an API key and use the WeatherAPI to extract daily and forecasted weather data.

4. Data Extraction
Write Python code to extract weather current and forecasted data from Weather API.

5. Data Transformation
Cleanse and manipulate the extracted data using Pandas functionalities.

6. Google Cloud Platform Introduction:
Introduce Google Cloud Platform, focusing on setting up a free trial account and understanding its core functionalities.
7. Load Raw Data in Data Lake
Write Python code to Load raw, unprocessed data into Cloud Storage.

8. Store Processed Data in Data Warehouse
Write Python code to Load Clean Data into BigQuery (Data Warehouse).

9. Cloud Deployment:
Deploy the ETL Data Pipeline as a Cloud Function for automated execution.

10. Automation with Cloud Scheduler: 
Set up Cloud Scheduler to automate the scraping process, ensuring daily data updates without manual intervention.

11. Data Visualization: Build an interactive dashboard with Looker Studio to visualize current and forecasted weather data.

12. Project Wrap-Up:
Review final steps and instructions for winding down the Google Cloud Platform Free Trial Account properly.

13. Portfolio Enhancement & Interview Prep: 
Learn how to upload your project to GitHub to showcase your technical skills to potential employers and prepare for common interview questions related to your project

Take your career to the next level
with better job opportunities and skills!

😍 Limited time offer!
1. Data Ingestion:
Raw Airbnb data is securely stored in a designated Cloud Storage bucket.

2. Scheduled Data Processing:
Cloud Scheduler triggers a Cloud Function, which automatically checks for new data daily.

3. Automated Transformation:
Upon detecting new data, the Cloud Function processes it, transforming raw data into a structured model.

4. Data Warehousing with BigQuery:
The transformed data seamlessly integrates into BigQuery, GCP's powerful data warehouse.

5. Visualization with Looker Studio:
Connect BigQuery with Looker Studio to create dynamic, insightful dashboards and visualizations.
6. Error Handling & Logging:
Robust error handling mechanisms ensure smooth operation. Logs are maintained for easy troubleshooting.

7. Version Control:
Implement version control for your codebase to track changes and facilitate collaboration.

8. Cost Monitoring:
Set up cost monitoring and budgets within GCP to avoid unexpected expenses.

9. Security and Access Control:
Apply proper security measures, including access control policies, to protect sensitive data and resources.

10. Documentation and Best Practices:
Provide comprehensive documentation for your project, including setup instructions, code explanations, and best practices. Create a code repository to impress potential employers.

Take your career and expertise to the next level!

1. Data Ingestion:
Raw Airbnb data is securely stored in a designated Cloud Storage bucket.

2. Scheduled Data Processing:
Cloud Scheduler triggers a Cloud Function, which automatically checks for new data daily.

3. Automated Transformation:
Upon detecting new data, the Cloud Function processes it, transforming raw data into a structured model.

4. Data Warehousing with BigQuery:
The transformed data seamlessly integrates into BigQuery, GCP's powerful data warehouse.

5. Visualization with Looker Studio:
Connect BigQuery with Looker Studio to create dynamic, insightful dashboards and visualizations.
6. Error Handling & Logging:
Robust error handling mechanisms ensure smooth operation. Logs are maintained for easy troubleshooting.

7. Version Control:
Implement version control for your codebase to track changes and facilitate collaboration.

8. Cost Monitoring:
Set up cost monitoring and budgets within GCP to avoid unexpected expenses.

9. Security and Access Control:
Apply proper security measures, including access control policies, to protect sensitive data and resources.

10. Documentation and Best Practices:
Provide comprehensive documentation for your project, including setup instructions, code explanations, and best practices. Create a code repository to impress potential employers.

Take your career and expertise to the next level!

WHAT YOU ARE GOING TO BUILD

Project architecture diagram:

   Project Workflow 

Here is the outline of the process you will follow to complete the project:
1. Getting Started:
Define the project, establish requirements, and devise an implementation strategy. Learn the essential steps for setting up and starting the project.

2. Mini-Course: API Fundamentals
Learn API fundamentals, what is an API, how data professionals uses APIs, how to get access and make API calls to extract data using Python and Postman.

3. Account Setup: Create an OpenWeather Account
Create a Free OpenWeather Account to get an API key and use the WeatherAPI to extract daily and forecasted weather data.

4. Data Extraction
Write Python code to extract weather current and forecasted data from Weather API.

5. Data Transformation
Cleanse and manipulate the extracted data using Pandas functionalities.

6. Google Cloud Platform Introduction:
Introduce Google Cloud Platform, focusing on setting up a free trial account and understanding its core functionalities.
7. Load Raw Data in Data Lake
Write Python code to Load raw, unprocessed data into Cloud Storage.

8. Store Processed Data in Data Warehouse
Write Python code to Load Clean Data into BigQuery (Data Warehouse).

9. Cloud Deployment:
Deploy the ETL Data Pipeline as a Cloud Function for automated execution.

10. Automation with Cloud Scheduler: 
Set up Cloud Scheduler to automate the scraping process, ensuring daily data updates without manual intervention.

11. Data Visualization: Build an interactive dashboard with Looker Studio to visualize current and forecasted weather data.

12. Project Wrap-Up:
Review final steps and instructions for winding down the Google Cloud Platform Free Trial Account properly.

13. Portfolio Enhancement & Interview Prep: 
Learn how to upload your project to GitHub to showcase your technical skills to potential employers and prepare for common interview questions related to your project

Take your career to the next level
with better job opportunities and skills!

😍 Limited time offer!

          Project Material         

We provide different types of content to serve learning purposes in the most efficient manner.

📝 Educational Text Material

We provide comprehensive step-by-step tutorials designed to guide you through building and deploying your project on the cloud. You'll receive detailed instructions for uploading your project to GitHub and gain access to common interview questions and answers related to the project. These resources are tailored to enhance your understanding and boost your job preparation effectively.

▶️ Comprehensive Video Lectures

For a more immersive learning experience, we offer video tutorials whenever needed. For instance, you can learn to build an interactive dashboard by closely following our step-by-step video lessons, making complex concepts easier to grasp and apply.

💯 Assessments & Quizes

Validate your grasp of the technologies and their strategic application with carefully designed assessments and quizzes integrated within the course structure.

🎓 Certificate of Completion

Upon successful completion of the course, you will be awarded a professional Certificate of Completion. Showcase your accomplishment on platforms like LinkedIn and other social networks.

         Project Material        

We provide different types of content to serve learning purposes in the most efficient manner.

📝 Educational Text Material

We provide comprehensive step-by-step tutorials designed to guide you through building and deploying your project on the cloud. You'll receive detailed instructions for uploading your project to GitHub and gain access to common interview questions and answers related to the project. These resources are tailored to enhance your understanding and boost your job preparation effectively.

▶️ Comprehensive Video Lectures

For a more immersive learning experience, we offer video tutorials whenever needed. For instance, you can learn to build an interactive dashboard by closely following our step-by-step video lessons, making complex concepts easier to grasp and apply.

💯 Assessments & Quizes

Validate your grasp of the technologies and their strategic application with carefully designed assessments and quizzes integrated within the course structure.

🎓 Certificate of Completion

Upon successful completion of the course, you will be awarded a professional Certificate of Completion. Showcase your accomplishment on platforms like LinkedIn and other social networks.

YOUR INSTRUCTOR

Mike Chionidis

Freelance Data & AI Engineer, specialized in Leading Teams and Building Products
About me

👋 I'm Mike, a Freelance Data & AI Engineer based in Greece. 


Throughout my career, I've worked with prominent clients like Publicis Groupe and delivered data products utilized by industry giants such as as Samsung, Three Mobile, and Western Union, and others. Within just two years of professional experience, I advanced to a Team Lead role, guiding a team of data professionals.

Previously, I've taught programming to university students to help them excel in their exams and assisted junior developers in kickstarting their careers.

My passion for sharing knowledge led to the establishment of DataProjects, with a clear purpose to help data enthusiasts secure their dream roles in the field. 

Let's embark on this learning adventure together, as we delve into the exciting world of data! 💫 
YOUR INSTRUCTOR

Mike Chionidis

Freelance Data Engineer, specialized in Leading Teams and Building Data Products
About me
👋 I'm Mike, a Freelance Data Engineer based in Greece. 

Throughout my career, I've worked with prominent clients like Publicis Groupe and delivered data products utilized by industry giants such as as Samsung, Three Mobile, and Western Union, and others. Within just two years of professional experience, I advanced to a Team Lead role, guiding a team of data professionals.

Previously, I've taught programming to university students to help them excel in their exams and assisted junior developers in kickstarting their careers.

My passion for sharing knowledge led to the establishment of DataProjects, with a clear purpose to help data enthusiasts secure their dream roles in the field. 

Let's embark on this learning adventure together, as we delve into the exciting world of data! 💫 
YOUR INSTRUCTOR

Mike Chionidis

Freelance Data & AI Engineer, specialized in Leading Teams and Building Products
About me
👋 I'm Mike, a Freelance Data & AI Engineer based in Greece. 

Throughout my career, I've worked with prominent clients like Publicis Groupe and delivered data products utilized by industry giants such as as Samsung, Three Mobile, and Western Union, and others. Within just two years of professional experience, I advanced to a Team Lead role, guiding a team of data professionals.

Previously, I've taught programming to university students to help them excel in their exams and assisted junior developers in kickstarting their careers.

My passion for sharing knowledge led to the establishment of DataProjects, with a clear purpose to help data enthusiasts secure their dream roles in the field. 

Let's embark on this learning adventure together, as we delve into the exciting world of data! 💫 
YOUR INSTRUCTOR

Mike Chionidis

Freelance Data & AI Engineer, specialized in Leading Teams and Building Products
About me
👋 I'm Mike, a Freelance Data & AI Engineer based in Greece. 

Throughout my career, I've worked with prominent clients like Publicis Groupe and delivered data products utilized by industry giants such as as Samsung, Three Mobile, and Western Union, and others. Within just two years of professional experience, I advanced to a Team Lead role, guiding a team of data professionals.

Previously, I've taught programming to university students to help them excel in their exams and assisted junior developers in kickstarting their careers.

My passion for sharing knowledge led to the establishment of DataProjects, with a clear purpose to help data enthusiasts secure their dream roles in the field. 

Let's embark on this learning adventure together, as we delve into the exciting world of data! 💫 

Frequently asked questions

1. How much Python and SQL knowledge is required?

A fundamental proficiency in Python, specifically with the Pandas library, is necessary. You should have experience working with Pandas DataFrames. In terms of SQL, a solid understanding of fundamental statements such as Select, From, Where, and Join, as well as familiarity with SQL tables, is recommended.

2. Will I need to subscribe to any Cloud services?

No, you won't need to pay for any Cloud subscriptions. Google Cloud offers all new users a $300 credit to use within their first 90 days. Simply create an account with your credit card, activate the trial, and follow the provided instructions to deactivate automated renewal, as demonstrated in the project videos.

3. How long will I have access to the project?

You will have access to the project and its materials for the duration of your subscription. This includes all future updates related to the project during your subscription period.

4. Do you offer trainings for professionals/businesses?

Yes, based on request, we offer professional training on Data/Cloud technologies. For inquiries regarding professional trainings, please reach out to us at info@dataprojects.io with your specific details, or using our Contact Form.

5. Have more questions?

For any additional inquiries or clarifications, feel free to contact us at info@dataprojects.io or using our Contact Form.

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