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DataScientest

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DataScientest

Avg Rating:5.0 ( 7 reviews )

DataScientest is a coding bootcamp offering 12-week, full-time courses in Data Analysis, Data Science, and Data Engineering. The DataScientest bootcamps are primarily conducted online, but have several in-person coaching sessions in Paris, France. Students can access a ready-to-code environment through DataScientest’s full SAAS platform that includes over 1,000 hours of learning content. While the bootcamps are full-time, DataScientist can adapt them to be 24- to 36-week part-time courses for students who need it. 

The Data Analyst bootcamp requires a prerequisite of Bac + 3 level with Mathematics or Computer Science. Bootcamp students will learn languages, such as Python, NumPy, Pandas, SQL, PySpark, CSS, HTML, PowerBi, Tableau, Dataiku, web scraping, and text mining. Students will also learn the art of storytelling and dashboard creation as well as machine learning concepts. Data Analyst students will learn how to develop segmentation criteria for a CRM database. They will also perform market research through data extraction from sites and social networks. 

The Data Scientist bootcamp requires a Bac + 5 level in Mathematics or Statistics and an understanding of programming concepts. Students will learn Python for Data Science and SAS/Excel, Object Programming, Web Scraping,  SQL, PyMongo, and PySpark. Students will learn methods of Data Visualization, such as Matpilotlib, Seaborn, and Bokeh. The Data Scientist bootcamp curriculum includes concepts of Machine Learning, such as clustering methods and concepts of Deep Learning, such as TensorFlow, CNN, RNN, and Gans. Finally, students will learn recommendation systems, reinforcement learning, Deep RL and algorithms. 

The Data Engineer bootcamp requires a Bac + 5 level in Computer Science and Bac + 3 in Statistics. Students will learn Bash, Python, Python object orientation, SQL, MongoDB, Cassandra, Elastic Search, and Neo4J. Data Engineer students will learn theories of big data architecture and streaming architecture, such as Hadoop, Hive, HBase, Pig, Spark, and Kafka. Finally, students will learn APIs with Flask, Docker, and Airflow. Data Engineer students work on developing segmentation criteria for a CRM database and perform market research through data extraction from sites and social networks. 

DataScientest course content is available in either French or English. DataScientest bootcamps are certified by Paris La Sorbonne University. Bootcamp graduates who pass a certification exam will receive a diploma from Sorbonne University upon program completion.

Recent DataScientest Reviews: Rating 5.0

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  • Data Analyst Bootcamp

    Apply
    HTML, Excel, CSS, SQL, Python
    OnlineFull Time12 Weeks
    Start Date None scheduled
    Cost3,795
    Class sizeN/A
    LocationOnline
    The Data Analyst bootcamp is a 12-week, full-time bootcamp and requires a prerequisite of Bac + 3 level with Mathematics or Computer Science. Bootcamp students will learn languages, such as Python, NumPy, Pandas, SQL, PySpark, CSS, HTML, PowerBi, Tableau, Dataiku, web scraping, and text mining. Students will also learn the art of storytelling and dashboard creation as well as machine learning concepts. Data Analyst students will learn how to develop segmentation criteria for a CRM database. They will also perform market research through data extraction from sites and social networks. 
    Financing
    DepositN/A
    Tuition PlansPayment in several instalments allowed
    Getting in
    Minimum Skill LevelRequires a prerequisite of Bac + 3 level with Mathematics or Computer Science.
    Placement TestNo
    InterviewNo
  • Data Engineer Bootcamp

    Apply
    MongoDB, Hadoop, SQL, Python
    OnlineFull Time12 Weeks
    Start Date None scheduled
    Cost4,495
    Class sizeN/A
    LocationOnline
    The Data Engineer course is a 12-week, full-time bootcamp and requires a Bac + 5 level in Computer Science and Bac + 3 in Statistics. Students will learn Bash, Python, Python object orientation, SQL, MongoDB, Cassandra, Elastic Search, and Neo4J. Data Engineer students will learn theories of big data architecture and streaming architecture, such as Hadoop, Hive, HBase, Pig, Spark, and Kafka. Finally, students will learn APIs with Flask, Docker, and Airflow. Data Engineer students work on developing segmentation criteria for a CRM database and perform market research through data extraction from sites and social networks. 
    Financing
    DepositN/A
    Tuition PlansPayment in several instalments allowed
    Getting in
    Minimum Skill LevelRequires a Bac + 5 level in Computer Science and Bac + 3 in Statistics.
    Placement TestNo
    InterviewNo
  • Data Scientist Bootcamp

    Apply
    Data Visualization, Excel, SQL, Python, Machine Learning
    OnlineFull Time12 Weeks
    Start Date None scheduled
    Cost4,495
    Class sizeN/A
    LocationOnline
    The Data Scientist bootcamp is a 12-week, full-time bootcamp that requires a Bac + 5 level in Mathematics or Statistics and an understanding of programming concepts. Students will learn Python for Data Science and SAS/Excel, Object Programming, Web Scraping,  SQL, PyMongo, and PySpark. Students will learn methods of Data Visualization, such as Matpilotlib, Seaborn, and Bokeh. The Data Scientist bootcamp curriculum includes concepts of Machine Learning, such as clustering methods and concepts of Deep Learning, such as TensorFlow, CNN, RNN, and Gans. Finally, students will learn recommendation systems, reinforcement learning, Deep RL and algorithms. 
    Financing
    DepositN/A
    Tuition PlansPayment in several installments allowed
    Getting in
    Minimum Skill LevelRequires a Bac + 5 level in Mathematics or Statistics and an understanding of programming concepts
    Placement TestNo
    InterviewNo
  • PAMIS • Resp Qualité • Student
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     Passées les premières certifications pour lesquelles l'examen en temps limité peut être source de stress et de contre-performance, le parcours est bien structuré, les exemples pertinents, et surtout le support est réactif (merci Daniel et Charles). 
    Quelques coquilles et approximations orthographiques à corriger mais le fond est robuste 
  • Nicolas • Data Scientist
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    Pédagogique, ludique, la formation nous force à repousser nos limites. L'équilibre entre quantité et difficulté est maîtrisé, donnant envie de s'investir sans avoir peur d'être découragé.
    Depuis la formation, je passe la moitié de mon temps de travail à retranscrire mes modèles sur Python !
  • Aurelia
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    Cette formation très complète que j’ai commencé il y a maintenant 5 mois m’a permis de rapidement monter en compétence et de mettre en application concrète mes sujets appris lors de la formation. Grace à des exercices pratiques centrés sur des problématiques orientées métiers.
  • Leslie • Data Scientits • Graduate
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    Cette formation hybride m’a permis de monter en compétence rapidement. Les modules sont agréables et claires, la plateforme est intuitive et facile d’utilisation, l’accompagnement et le support sont personnalisés et continus ! Je recommande fortement DataScientest à ceux qui veulent se former efficacement au métiers des Data Science.
  • Super formation
    - 5/4/2020
    Shai Laloum • Graduate
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     Cette formation a parfaitement répondu à mes attentes. Le format est idéal et permet une flexibilité bienvenue pour des emplois du temps chargés. Les cours sont très didactiques et adaptés à tous les niveaux. Je recommande cette formation qui sera, sans aucun doute, une plus-value pour la suite de ma carrière. 
  • Excellent
    - 5/4/2020
    Nicolas
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    Les cours sont clairs et agréables à lire, et les mises en pratique permettent de bien appréhender les outils présentés. La formation permet de comprendre les enjeux (la puissance, les possibilités offertes) des technos présentées et de pouvoir ensuite les utiliser dans d'autres contextes que les jeux de données des cours ; les cours donnent également les clé pour pouvoir approfondir de son côté les notions qui m'intéressent le plus.
  • Marylene Henry • Statisticienne • Graduate
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    Je suis ravie de cette expérience de formation. C’est une chance d’accéder à la fois à une formation de qualité et à un soutien aussi efficace. Pourtant mes compétences en Python sont limitées(je fais traditionnellement du R) mais j’ai fait un bond avec cette formation. Tout est expliqué ce qui permet de voir des progrès et de rester motivée. La formation fournit de solides bases que j’aurai le loisir d’approfondir par la suite.