Artefact School of Data

A Data Analytics bootcamp offers participants an intensive program focusing on essential skills for data analytics. The curriculum covers data types, programming languages like Python and R, data visualization, statistical analysis, and database management. Participants gain hands-on experience in data wrangling and cleaning, as well as applying machine learning techniques to analyze data. The bootcamp emphasizes ethical considerations and privacy concerns in data analytics. It concludes with a capstone project where participants showcase their abilities to solve real-world data analytics problems. Graduates are well-equipped to pursue careers as data analytics engineers, driving data-informed decision-making in organizations.

Syllabus:
Business Intelligence
SQL & Data Warehouse
Data Sourcing
Data Visualization
Python Programming
Machine Learning
Culture Data

This 400 hours course is the perfect track for beginners with no coding background. Through an accelerated intensive learning experience, you will gain a solid knowledge of data science with Python.

Without prior experience, you will soon be able to work with multiple data sources, create compelling visualizations, perform valuable exploratory data analysis, and implement machine learning models. The course covers the most important tools used in the industry to help you build solid foundations, with an emphasis on learning by doing and our project driven approach will help you build a portfolio as you learn. Our instructors have deep practical and theoretical knowledge on the material covered.

We bring you the technical skills you need to join a growing tech startup or launch your own data-science based project. Last but not least, you will enjoy the strong family-like atmosphere in the space

Syllabus:
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01 - Python Foundations : data types and structures, control flow, functions and modules, OOP, Git and Github.

02 - Data collection : interactions with files, websites scraping, communication with APIs, database queries, regular expressions, big data with PySpark.

03 - Data analysis and visualization: Numpy, Pandas, Matplotlib, Seaborn, Tableau, exploratory data analysis (EDA), introduction to statistics.

04 - Machine Learning with Scikit-Learn: concepts and principles, classification, regression, train-test, Naive Bayes, cross-validation, feature selection, hyper parameters, PCA, unsupervised clustering, unsupervised dimensionality reduction, recommandation, deployment, regularization, anomaly detection, customer churn, random forest, decision trees, fraud detection, gradient boosting, times series.

05 - Natural Langage Processing (NLP) with NLTK/spaCy/Gensim/AutoML: preprocessing, tokenization, n-gram, lemmatization, latent semantic analysis, topic modeling, entity sentiment analysis.

06 - Deep Learning Introduction with Tensorflow: perceptron, multi-layer, convolutional neural networks, Docker and AWS deployment.

Our Data Scientist bootcamp provides participants with a comprehensive understanding of data science concepts and techniques. The program covers programming skills in Python and R, statistical analysis, and machine learning algorithms. Participants also delve into deep learning and neural networks. They learn how to apply these advanced techniques to solve complex problems and extract valuable insights from data. The bootcamp emphasizes hands-on projects and real-world applications, allowing participants to build a strong portfolio of data science projects. By completing the bootcamp, participants are prepared to tackle data-driven challenges and make informed decisions as data scientists.

Syllabus:
Data Science & Python
Data Management
Data Analyses
Machine Learning
NLP
Deep Learning
Cloud and Big Data
ML Engineering