BOOTCAMP: Data Scientist
The Data Scientist training at Datakoo is designed for a wide range of individuals: professionals looking to refine their skills, students eager to deepen their knowledge in data analysis, as well as all enthusiasts who are eager to dive into the fascinating world of Machine Learning.
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The Role of a Data Scientist
Mission
🌍 In a world where every click 🖱️, every purchase 💳, and even every movement 🚶♂️ is recorded, the ability to decipher these mountains of data 📊 becomes an invaluable asset 💎.
🔬 This is where the role of the Data Scientist comes into play. This profession, at the intersection of technology 💻, statistics 📈, and business strategy 🏢, is the linchpin that transforms raw information into insightful gems 🧠✨.
🌐 Becoming an expert in Data Science not only means mastering advanced tools 🛠️ and techniques 🔎 but also possessing the strategic vision 🌟 to guide businesses in this digital era 📡.
🎓 Datakoo Training is your gateway 🌉 to this captivating universe 🌌.
📚 Our training covers both the basics and the complex, from data exploration in Python 🐍 to the application of Machine Learning 🤖.
But beyond technical skills, we prepare you to become the strategist 🧐 that every modern company seeks: capable of translating numbers into strategies 🗺️, navigating the sea of data 🌊 to find uncharted opportunities 🚀.
✨ Join us, and carve your place in the future of the industry 🌐💼.
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📚 Course content
Algorithmic Expertise
Dive into Python, R and SQL, decrypting relational and NoSQL databases to extract essential information.
Art of Visualization
Translate data into impactful stories with Tableau and Power BI, making every analysis visually compelling.
Statistical Strategy
From regression to neural networks, navigate through advanced techniques to discover hidden patterns.
Corporate Vision
Link your analytics to the business impact, aligning each discovery with the company’s overall strategy.
Cloud Pioneer
Leverage AWS, Azure and GCP to manipulate huge datasets, preparing for the future of data.
Analytical Acuity
Sharpen your mind to tackle data challenges with critical thinking, turning ambiguity into clarity.
The data scientist profession in a few numbers
Attractive Salaries
10000
€
The average salary of a Data Scientist in France can vary based on experience and region. On average, a junior Data Scientist can earn between €40,000 and €50,000 per year. With several years of experience, this figure can exceed €70,000 or even €90,000 for the most experienced profiles.
Increasing Demand
0
%
Job Offers for Data Scientists have experienced exponential growth in France in recent years. According to some reports, the demand for this position has increased by at least 30% each year.
Diverse Skills
0
%
Just like elsewhere in the world, Python and R are the most favored programming languages by Data Scientists in France. According to certain surveys, nearly 70% of professionals in France use Python.
Format & Prerequisites
Format: 1 Day
1-Day Data Scientist aculturation
- Introduction to Data Science: Understand the role, responsibilities, and impact of a data scientist.
- Data Exploration with Python: Dive deep into data analysis using Pandas and understand array programming with NumPy.
- Data Visualization: Harness the power of Matplotlib and Seaborn for compelling visual data storytelling.
- Machine Learning Overview: Discover the fundamentals, types, and applications of machine learning in real-world scenarios.
- Hands-on Session: Analyze a sample dataset integrating the day's topics, showcasing a data scientist's workflow.
- Discussion and Q&A: Address queries, share resources for further learning, and discuss potential career paths in data science.
Format : 2 Days
Day 1: Foundations of Data Science
- Introduction to Data Science: Role, responsibilities, and significance of data scientists in today's world.
- Data Exploration with Python: Understanding data structures, cleaning data, and preliminary analysis using Pandas.
- Data Visualization: Techniques for data visualization using Python libraries, including Matplotlib and Seaborn.
- Hands-on Workshop: Analyze a real-world dataset integrating the day's topics.
Day 2: Embarking on the Machine Learning Journey
- Overview of Machine Learning: Understanding different types of machine learning, including supervised, unsupervised, and reinforcement learning.
- Building ML Models: Introduction to Scikit-Learn, data preprocessing, and building basic models.
- Model Evaluation: Dive deep into concepts like accuracy, precision, recall, and F1 score. Understand overfitting and how to prevent it.
- Hands-on Workshop: Build, evaluate, and fine-tune a machine learning model using Scikit-Learn.
- Discussion and Q&A: Addressing queries, discussing case studies, and exploring advanced topics for future learning.
Format: 4 Days
Day 1: Foundations of Data Science and Data Visualization
- Introduction to Data Science: Understanding the data-driven decision-making process.
- Data Exploration with Python: Dive deep into Pandas and NumPy for data manipulation.
- Data Visualization: Techniques for creating intuitive visuals using Matplotlib and Seaborn.
- Workshop: Guided hands-on activities on data manipulation and visualization.
Day 2: Embarking on Machine Learning
- Introduction to Machine Learning: Understanding ML, its types, and applications.
- Supervised Learning: Delve into regression and classification algorithms.
- Model Evaluation and Validation: Understand key metrics to evaluate model performance.
- Workshop: Building a supervised learning model from scratch.
Day 3: Advanced Techniques and NLP
- Unsupervised Learning: Discover clustering and dimensionality reduction techniques.
- Introduction to Natural Language Processing (NLP): Basics of text processing and sentiment analysis.
- Workshop: Analyzing text data using basic NLP techniques.
Day 4: Advancing in Machine Learning and Final Presentations
- Advanced Machine Learning: Dive into ensemble methods and other advanced techniques.
- Real-world Case Studies: Analyzing real-world problems and discussing solutions.
- Final Projects Presentation: Teams present their projects, followed by discussions and feedback.
Prerequisites
Prerequisites:
- A strong foundation in mathematics and statistics
- Understanding of fundamental programming principles
- Knowledge of databases is a plus, but not mandatory
🚀 Why Choose Datakoo Training's Course?
proven expertise
Our trainers, with years of experience in the field, combine solid theory and proven practice to offer high-level teaching.
innovative pedagogy
The training is structured around interactive pedagogical approaches, combining real-life case studies, practical workshops, and tutoring sessions, to ensure a deep and applied understanding of the concepts.
market relevance
Designed to meet today’s business needs, our training specifically prepares you for the real challenges of the data world, making you immediately operational.
ongoing support
At Datakoo, your learning goes beyond training. We value lifelong learning and are here to answer your questions in a professional context. Get post-training support and regular updates on our platform. With Datakoo, you have a constant ally in your professional progression.
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🗓 Schedule Your Consultation!
Do you have questions? Do you want to learn more about our courses or discuss a specific project? Schedule a personalized session with our team.
We look forward to collaborating with you and assisting you on your learning journey with Datakoo Training.
Do you want to take your skills to the next level today?
Discover the future of data training. With Datakoo, every lesson is an opportunity, every module a step towards excellence. You have the potential; we have the tools. Start your transformation today!