Curriculum
Sprint 1
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Curriculum
Sprint 1
Programming with Python
45h
Fundamentals of Python
Statistics
Data Quality (optional)
Sprint 2
Datavisualisation
35h
Matplotlib
Seaborn
Additional Matplotlib (optional)
Bokeh (optional)
The Art of Storytelling (optional)
Plotly (optional)
Sprint 3
Supervised Machine Learning
35h
Machine Learning Data Analyst
Algorithms and Methodology for Classification with Scikit-Learn (optional)
Pipeline (optional)
Streamlit (optional)
Sprint 4
Data Analysis
25h
Data Analysis
Time Series with Statsmodels (optional)
Sprint 5
Extraction and Management of Data
25h
Text Mining
Webscraping with BeautifulSoup
Web Scraping with Selenium (optional)
Sprint 6
Business Intelligence
30h
Business Intelligence
Power BI
Looker Studio
Tableau (optional)
No-Code Automation with Make (optional)
Sprint 7
Database / Big Data
SQL Language
Fundamental Theory of Data Integration (optional)
Curriculum
Sprint 1
Programming
50h
Python Fundamentals
NumPy
Pandas
Sprint 2
Data Visualisation
30h
Matplotlib
Seaborn
Bokeh (optional)
Sprint 3
Machine Learning
45h
Classification models and algorithms
Advanced classification of models
Clustering methods
Regression methods
Sprint 4
Advanced Machine Learning
45h
Time Series with Statsmodels
Text Mining
Size Reduction Methods
Machine Learning and Graph Theory with NetworkX (optional)
Sprint 5
Data Engineering
25h
SQL Language
PySpark
Sprint 6
Deep Learning
60h
Deep Learning with Keras framework
TensorFlow
Sprint 7
Complex System and AI
25h
Introduction to Reinforcement Learning
Deep Reinforcement Learning
Curriculum
Sprint 1
Programming
40h
Python
Web Scraping
Sprint 2
Advanced Tools
20h
Git
GitHub
Unit Tests
Linux System and Bash Script
Sprint 3
Big Data Variety
50h
SQL
MongoDB
HBase
ElasticSearch
Neo4J
Sprint 4
Big Data Volume
50h
Hadoop and Hive
PySpark
Java Spark
Sprint 5
Big Data Velocity
20h
Streaming architecture
Kafka
Spark Streaming
Sprint 6
Data Science
50h
Statistics
Machine Learning
Data Visualization
Sprint 7
Deployment
35h
APIs
Docker
Sprint 8
Automation and Orchestration
25h
Airflow
Kubernetes
Curriculum
Sprint 1
Programming with Python
45h
Fundamentals of Python
Statistics
Data Quality (optional)
Sprint 2
Data Vizualisation
35h
Matplotlib
Seaborn
Additional Matplotlib (optional)
Bokeh (optional)
The Art of Storytelling (optional)
Plotly (optional)
Sprint 3
Supervised Machine Learning
35h
Machine Learning Data Analyst
Algorithms and Methodology for Classification with Scikit-Learn (optional)
Pipeline (optional)
Streamlit (optional)
Sprint 4
Data Analysis
25h
Data Analysis
Time Series with Statsmodels (optional)
Sprint 5
Extraction and Management of Data
25h
Text Mining
Webscraping with BeautifulSoup
Web Scraping with Selenium (optional)
Sprint 6
Business Intelligence
30h
Business Intelligence
Power BI
Looker Studio
Tableau (optional)
No-Code Automation with Make (optional)
Sprint 7
Database / Big Data
25h
SQL Language
Fundamental Theory of Data Integration (optional)
Sprint 8
Fundamentals of Programming
Linux & Bash
API
Git / GitHub (optional)
Unit-Tests (optional)
Sprint 9
Data Integration
SQL Language
Fundamentals of Data Integration
NoSQL Databases (MongoDB) (optional)
Sprint 10
SQL / NoSQL
Snowflake
BigQuery
Data Warehousing with DBT (ELT)
Talend Open Studio
Best Practices in Data Warehousing
Sprint 11
Practical Data Warehousing
ETL with PySpark
Airflow
From Data Integration to Data Analytics
Curriculum
Sprint 1
Python Fundamentals
40h
Programming
NumPy
Pandas
Sprint 2
Data Visualisation
20h
Matplotlib
Seaborn
Plotly (optional)
Sprint 3
Programming Tools
20h
Git
GitHub
Unit Tests
Linux System and Bash Script
Sprint 4
Machine Learning
30h
Classification Models and Algorithms
Clustering Methods
Regression Methods
Sprint 5
Advanced Machine Learning
30h
Time Series with Statsmodels
Anomaly Detection
Size Reduction Methods
Sprint 6
Applied Machine Learning
20h
Text Mining
Webscraping
Ethics & Interpretability
Sprint 7
Complex Models
20h
Recommender Systems
Reinforcement Learning
Graph Theory
Sprint 8
Deep Learning Fundamentals
40h
Dense Networks
Convolution Networks
TensorFlow
Sprint 9
Data Engineering
30h
SQL
API
PySpark
Sprint 10
MLOps
30h
MLFlow
Docker
Sprint 11
Linux & Bash
40h
Programmation Linux & Bash
Docker
MLFlow
Unit Testing
Sprint 12
Versioning & Isolation
35h
DVC & DagsHub
Jenkins
Airflow
Sprint 13
Deployment & Model Serving
35h
BentoML
Prometheus & Grafana
SQL
Sprint 14
Scaling & Orchestration Platform
25h
Kubernetes
ZenML
Weights & Biases
AWS Cloud Practitioner
Curriculum
Sprint 1
Introduction to Data Marketing
Introduction to Data in Business
Fundamentals of Data Architecture
The Different Types of Data Consumption
Sprint 2
Programming Languages
Google Sheets for Digital Marketing
Fundamentals of Python
Webscraping with BeautifulSoup (optional)
Data Manipulation with Pandas (optional)
SQL for Data Analysis (optional)
Sprint 3
Tracking & Data Analysis
Google Analytics 4 (GA4)
Google Tag Manager (GTM)
Sprint 4
Main Sources of Acquisition
Keys to Traffic Acquisition
Social Media Ads
SEA with Google Ads
Sprint 5
Prompt Engineering
Overview of No-Code Tools
Fundamentals of Generative AI and Prompting
Data API Fundamentals
Automation and AI Agents with n8n
Sprint 6
AI, Growth Hacking & Marketing Automation
Marketing Strategy
CRM & Marketing Automation
Content Generation & Automation with Make
Website Generation with v0
Webscraping with BeautifulSoup (optional)
Sprint 7
Dataviz, Business Intelligence & Regulations
Introduction to Business Intelligence
Looker Studio
UX & UI Design
GDPR, Ethics and AI Act
Power BI (optional)
Sprint 8
Data Product Management & Data Governance
Data Product Manager
Project Management
Data Governance
Agile Method
Curriculum
Sprint 1
MLOps – Fundamentals
40
Programmation Linux & Bash
Docker
MLflow
Unit Testing
Sprint 2
Versioning & Isolation
35
DVC & DagsHub
Airflow
Jenkins
Sprint 3
Deployment & Model Serving
35
BentoML
Prometheus & Grafana
SQL
Sprint 4
Scaling & Orchestration Platform
25
Kubernetes
ZenML
ZenML
AWS Cloud Practitioner
Curriculum
Sprint 1
Fundamentals of Programming (Python)
Sprint 2
Data Integration & SQL/NoSQL
Sprint 3
Practical Data Warehousing
Curriculum
Sprint 1
Introduction to Linux
Sprint 2
Linux Administration
Sprint 3
Continuous Integration
Sprint 4
GitOps
Sprint 5
Introduction to Cloud
Sprint 6
DevOps Cloud
Curriculum
Sprint 1
Programming
40
Python
Web Scraping
Sprint 2
Advanced Tools
20
Git
Linux System and Bash Scripting
Github
Sprint 3
Big Data Variety
50
SQL
MongoDB
HBase
ElasticSearch
Neo4J
Sprint 4
Batch & Streaming – Part 1
50
Hadoop and Hive
PySpark
Scala Spark
Sprint 5
Batch & Streaming – Part 2
20
Streaming Architecture
Streaming with Spark
Webscraping
Sprint 6
Cloud AWS
70
AWS Solutions Architect
Sprint 7
Machine Learning
60
Statistics
Data Visualization
Machine Learning
MLFlow
Sprint 8
DevOps – Virtualisation
50
AWS Solutions Architect
Securing APIs
Docker
Kubernetes
Sprint 9
CI/CD and Monitoring
40
Airflow
GitLab
Unit Testing with Python
Prometheus & Grafana
Sprint 10
Virtualization, Linux systems & agility
68
Virtualisation & Vagrant
Administration of Linux Systems
NGINX
Sprint 11
GitLab, Jenkins & Automation
76
Jenkins
GitLab
Terraform
Ansible
Sprint 12
Monitoring
45
Prometheus
Grafana
Datadog
Sentry (optional)
Sprint 13
Cloud DevOps
45
AWS Cloud Basics
AWS Lambda
AWS CodePipeline
AWS API Gateway
AWS CloudFormation
Curriculum
Sprint 1
Application Development with Python
53
FastAPI
Linux and Bash
Virtualization and Vagrant
Python Basic and Advanced
Sprint 2
Linux Systems and Agility
53
Administration of the Linux Systems
NGINX
Data Structure and Storage (optional)
Sprint 3
Databases
38
SQL Language
PostgreSQL
MongoDB
Neo4J (optional)
Elasticsearch (optional)
Sprint 4
CI/CD
53
Git/GitHub
Docker
GitLab
Kubernetes
Jenkins
Unit Tests (optional)
Sprint 5
Cloud AWS
53
AWS Cloud Practitioner
AWS Solutions Architect
Sprint 6
Automation
53
Terraform
Ansible
Sprint 7
Monitoring
45
Prometheus
Grafana
Datadog
Sentry (optional)
Sprint 8
Cloud DevOps
45
AWS – Lambda
AWS – API Gateway
AWS – CodePipeline
AWS – CloudFormation
AWS – Migration to the Cloud (optional)
AWS – X-Ray (optional)
AWS – CodeStar (optional)
Curriculum
Sprint 1
Familiarization with the Cloud
Sprint 2
Introduction to AWS Core Concepts
Sprint 3
First Steps on the AWS Architecture and First Applications
Sprint 4
Design of Network Architectures
Sprint 5
























