1. Data Science Foundations and Environment Setup (Week 1)
- •Introduction to data science concepts and workflow
- •Setting up Anaconda and Jupyter Notebook
- •Working with Python basics for data tasks
- •Using notebooks for practice and analysis
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Data Science Training in Frankfurt with Certification
Build practical data science skills in Frankfurt using Python, R, SQL, Pandas, NumPy, Scikit-learn, TensorFlow, Keras, PyTorch, Tableau, Power BI, Docker, Git, GitHub, Apache Spark, Hadoop, and cloud tools like AWS SageMaker and Google Cloud Vertex AI. Learn to clean data, build models, create dashboards, and work through real project-style exercises from an industry-focused data science course in Frankfurt.
4.7/5 from 1,432 reviews
Practical data science training in Frankfurt with Python, SQL, and analytics tools
Hands-on work with Pandas, NumPy, Scikit-learn, TensorFlow, Keras, and PyTorch
Dashboard and reporting practice using Tableau, Power BI, and Excel
Project-based learning with Jupyter Notebook, Git, GitHub, and Docker
Career support for data analyst, data scientist, BI, and machine learning roles
Job Interview
Guarantee Program
14,200+ (Placed)
Freshers to IT
7,100+ (Placed)
Non-IT to Tech
5,800+ (Placed)
Career Gap Fillers
6,400+ (Placed)
Upskilling Success
24,999₹
In 90 Days + Placement
Course Fee:₹24,999
Duration:60 Days
Mode:Classroom & Online
Free Session
1 Hour Training Session
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Placement Assistance for Data Science Careers in Frankfurt
Learning data science is only useful when it leads to a role that matches your skills. Inventateq keeps the focus on placement readiness, so learners in Frankfurt can present their Python, SQL, analytics, and model-building work clearly in interviews. Our support covers the full job search process, from resume preparation to mock interviews and role guidance for data analyst, BI analyst, and junior data scientist positions.
Our Signature Career Support:
- Resume preparation for data science and analytics roles
- Mock interviews based on Python, SQL, and model-building tasks
- Portfolio guidance using notebooks, dashboards, and project work
- Career mentoring for junior data analyst and data scientist roles
- Interview readiness for BI, analytics, and machine learning profiles
Data Science Salary Insights in Frankfurt
Frankfurt hires for data science across finance, consulting, operations, business intelligence, and product teams. As experience grows, salary moves up with better project exposure, stronger SQL and Python skills, and the ability to handle model deployment and analytics delivery.
Average Data Science Salary by Experience
Data Science Salary Insights in Frankfurt
Frankfurt hires for data science across finance, consulting, operations, business intelligence, and product teams. As experience grows, salary moves up with better project exposure, stronger SQL and Python skills, and the ability to handle model deployment and analytics delivery.
Average Data Science Salary by Experience
Why Students Choose Our Data Science Course in Frankfurt?
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Success Result: Our students are competing at global levels. Watch their placement journey here.
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About Inventateq Data Science Training Institute in Frankfurt
Inventateq teaches data science in a practical sequence, starting with core tools and moving into modeling, dashboards, and deployment. The course content is built around real work with Python, SQL, Pandas, machine learning libraries, visualization tools, and cloud platforms, so learners do not stop at theory. Students get guided practice, assignments, and project-oriented training that fits entry-level as well as career-switcher goals in Frankfurt.
We stand apart through our commitment to:
- Learn Python, SQL, and core data preparation skills from the ground up
- Work on analytics, visualization, and machine learning tasks step by step
- Build confidence with notebook-based practice and guided assignments
- Get mentor support while solving project and interview questions
- Choose flexible learning options with placement-oriented training
Live Online
Remote Learning
AI Online Live Classes
Live online classes for learners in Frankfurt follow the same practical curriculum as the classroom program. You can attend from home, ask questions in real time, and complete assignments using the same tools covered in training, including Jupyter Notebook, Tableau, Power BI, and Python.
Live interactive classes with practical coding demonstrations
Recorded sessions available for revision and practice
Weekly assignments with mentor feedback and guidance
Real projects covering Generative AI, LLMs, and Agentic AI
Online career guidance and interview preparation support
Data Science Training Program in Frankfurt
Students and fresh graduates
Good for learners starting with Python, SQL, and analytics fundamentals.
Working professionals
Useful for those shifting into data analyst, BI, or data science roles.
Non-technical graduates
Fits learners who want a step-by-step path into practical data science.
IT professionals
Helps developers, testers, and support engineers move into analytics and ML.
Business and finance learners
Useful for people who want to use data for reporting, forecasting, and decision-making.
Quick Highlights of Inventateq Data Science Course in Frankfurt
Course Duration
Duration: Structured training schedule with live practical sessions
Mode: Offline classroom and live online training
Batch Options: Weekday and weekend batches available
Approach: Theory, practicals, assignments, and certification
No prior data science experience is required to start.
Data Science Course Curriculum in Frankfurt
W1
2. Python for Data Handling (Week 2)
- •Python syntax for analysis work
- •Lists, dictionaries, loops, and functions
- •Writing reusable code for data processing
- •Preparing scripts for notebook-based exercises
3. Data Analysis with Pandas and NumPy (Week 3)
- •Loading and inspecting datasets
- •Data cleaning and transformation with Pandas
- •Numerical operations with NumPy
- •Working through missing values and structured data
4. SQL and Database Fundamentals (Week 4)
- •SQL basics for querying data
- •Working with MySQL and PostgreSQL
- •Filtering, joins, grouping, and aggregations
- •Using databases for analytics tasks
5. Data Visualization and Reporting (Week 5)
- •Creating charts and reports in Excel
- •Dashboard practice with Tableau
- •Dashboard practice with Power BI
- •Turning data findings into business-friendly visuals
6. Statistics for Data Science (Week 6)
- •Core statistical concepts for analysis
- •Descriptive statistics and interpretation
- •Probability basics for data work
- •Using statistics to support model decisions
7. Machine Learning Foundations (Week 7)
- •Introduction to supervised and unsupervised learning
- •Model building with Scikit-learn
- •Training, testing, and evaluation basics
- •Understanding common ML workflow steps
8. Regression and Classification (Week 8)
- •Linear and logistic regression concepts
- •Classification workflow and metrics
- •Feature handling for model performance
- •Applying models to practical datasets
9. Advanced Machine Learning and Model Tuning (Week 9)
- •Tree-based methods and ensemble ideas
- •Model selection and tuning basics
- •Improving model accuracy through iteration
- •Comparing different algorithms for a problem
10. Deep Learning Basics (Week 10)
- •Introduction to neural network concepts
- •Working with TensorFlow and Keras
- •Using PyTorch at a basic applied level
- •Understanding deep learning use cases
11. Big Data and Distributed Processing (Week 11)
- •Introduction to Apache Spark
- •Understanding Hadoop in the data ecosystem
- •Handling larger datasets and workflows
- •Using big data tools in analytics environments
12. Version Control and Collaboration (Week 12)
- •Using Git for code tracking
- •Publishing and managing work on GitHub
- •Keeping project files organized
- •Collaborating on data projects safely
13. Cloud Tools and Deployment Basics (Week 13)
- •Introduction to Docker for environment handling
- •Using AWS SageMaker for model workflows
- •Exposure to Google Cloud Vertex AI
- •Preparing data projects for deployment contexts
14. Capstone Project and Interview Preparation (Week 14)
- •End-to-end data science project work
- •Applying tools from the full curriculum
- •Resume preparation for data roles
- •Interview practice and final certification review
Rated 4.9/5
Why Inventateq for Data Science Training in Frankfurt?
Inventateq focuses on practical learning that matches real data jobs, not just classroom definitions. The training follows a tool-first approach with Python, SQL, visualization, machine learning, and cloud exposure taught in a sequence that supports project work.
Why Students Trust Inventateq Frankfurt
- Trainers explain concepts clearly and keep sessions practical
- Curriculum stays aligned with current data science tools and job needs
- Supportive learning environment with time for doubt clearing
- Assignments and projects help learners build usable experience
- Placement guidance is built into the training process
Build Job-Ready Data Science Skills in Frankfurt
Learners leave with practice in data handling, analysis, model building, and reporting. The course is designed so students can talk about real tools and real project steps during interviews.
Work with Real Data Tools
Practice Python, SQL, Pandas, NumPy, and notebook-based workflows used in data science work.
Build Analytics and Dashboards
Create reports and visual outputs with Tableau, Power BI, and Excel.
Train Machine Learning Models
Use Scikit-learn and related libraries to build and evaluate models.
Understand Deep Learning Basics
Get exposure to TensorFlow, Keras, and PyTorch in applied training.
Use Big Data and Cloud Tools
Learn the basics of Spark, Hadoop, Docker, and cloud model platforms.
Prepare for Interviews and Projects
Finish with resume support, project review, and role-focused interview practice.
Data Science Training Certification
The certification shows that the learner has completed structured training in data science tools, analysis methods, visualization, machine learning, and project work. It supports employability by documenting practical exposure to the tools used in entry-level analytics and data science roles.
Python, Pandas, and NumPy
Earn this certificate upon successful completion of our training program.
SQL, Tableau, and Power BI
Validate your skills with recognized industry credentials.
Scikit-learn, TensorFlow, Keras, and PyTorch
Earn this certificate upon successful completion of our training program.
Git, GitHub, Docker, and cloud tools like AWS SageMaker
Validate your skills with recognized industry credentials.
Detailed Insights: Data Science Training in Frankfurt
Students Frequently Asked Questions
Do I need a technical background for this data science course?
No, you do not need a full technical background to begin. The training starts with the foundations and gradually moves into tools and models. If you are consistent with practice, the course is built to be approachable for beginners.
Will I get hands-on project work in Frankfurt?
Yes, the course is practical and includes assignments and project-style exercises. You will work with notebooks, SQL, dashboards, and machine learning tasks. The aim is to help you explain your work clearly in interviews.
Does Inventateq provide placement assistance for data science roles?
Yes, placement support is part of the course structure. You get help with resume preparation, mock interviews, and role guidance for data analyst, BI, and junior data scientist positions. The support is focused on making your skills visible to employers.
Can working professionals attend the course?
Yes, working professionals can join through flexible batch options. Weekday and weekend training formats help you balance learning with your current schedule. Live online classes also make it easier to attend from Frankfurt.
What tools will I learn in this training?
The course covers Python, R, SQL, Anaconda, Jupyter Notebook, Pandas, NumPy, Scikit-learn, TensorFlow, Keras, PyTorch, Tableau, Power BI, Excel, Spark, Hadoop, Git, GitHub, Docker, AWS SageMaker, and Google Cloud Vertex AI. These tools support analysis, modeling, reporting, and deployment basics. You will use them in a structured way across the curriculum.
How long is the course and what learning modes are available?
The course follows a structured schedule with both offline classroom and live online options. You can choose weekday or weekend batches depending on your availability. This gives learners in Frankfurt a practical way to complete the training without disrupting work or studies.
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