À propos de ce cours

13,440 consultations récentes

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.

Niveau intermédiaire

Python programming (beginners)

Investment theory (recommended)

Statistics (recommended)

Approx. 10 heures pour terminer

Recommandé : 4 weeks of study, 2 hours per week...

Anglais

Sous-titres : Anglais

Ce que vous allez apprendre

  • Check

    Learn what alternative data is and how it is used in financial market applications. 

  • Check

    Become immersed in current academic and practitioner state-of-the-art research pertaining to alternative data applications.

  • Check

    Perform data analysis of real-world alternative datasets using Python.

  • Check

    Gain an understanding and hands-on experience in data analytics, visualization and quantitative modeling applied to alternative data in finance

Compétences que vous acquerrez

Advanced vizualisationBasics of consuption-based alternative dataText mining methodologiesWeb-scritpting tools

100 % en ligne

Commencez dès maintenant et apprenez aux horaires qui vous conviennent.

Dates limites flexibles

Réinitialisez les dates limites selon votre disponibilité.

Niveau intermédiaire

Python programming (beginners)

Investment theory (recommended)

Statistics (recommended)

Approx. 10 heures pour terminer

Recommandé : 4 weeks of study, 2 hours per week...

Anglais

Sous-titres : Anglais

Programme du cours : ce que vous apprendrez dans ce cours

Semaine
1

Semaine 1

5 heures pour terminer

Consumption

5 heures pour terminer
10 vidéos (Total 74 min), 5 lectures, 1 quiz
10 vidéos
What is consumption data?8 min
Geolocation and foot-traffic5 min
Lab session: Introduction to the Uber Dataset6 min
Lab session: Points of Interest5 min
Lab session: Mapping Data with Folium9 min
Lab session: Testing Seasonality11 min
Application: Consumption data and earning surprises7 min
Application:Consumption-based proxies for private information and managers behavior7 min
Application: Additional applications of consumption data7 min
5 lectures
Material at your disposal5 min
Note about HeatMapWithTime2 min
Extra materials on consumption1 h
Additional resources on the interest of real-time corporate sales'measures1 h
Additional resources on Predicting Performance using Consumer Big Data1 h
1 exercice pour s'entraîner
Graded Quiz on Consumption30 min
Semaine
2

Semaine 2

3 heures pour terminer

Textual Analysis for Financial Applications

3 heures pour terminer
8 vidéos (Total 75 min), 2 lectures, 1 quiz
8 vidéos
Introduction to textual analysis3 min
Processing text into vectors12 min
Normalizing textual data5 min
Lab session: Introduction to Webscraping11 min
Lab session: Applied Text Data Processing11 min
Lab session: Company Distances and Industry Distances15 min
Application: applying similarity analysis on corporate filings to predict returns9 min
2 lectures
Extra materials on Textual Analysis for Financial Applications1h 10min
Additional resources on textual analysis for financial applications1 h
1 exercice pour s'entraîner
Graded Quiz on Textual Analysis for Financial Applications
Semaine
3

Semaine 3

3 heures pour terminer

Processing Corporate Filings

3 heures pour terminer
8 vidéos (Total 69 min), 3 lectures, 1 quiz
8 vidéos
Lab session: Working with 10-K Data7 min
Lab session: Applications of TF-IDF11 min
Lab session: Risk Analysis9 min
Lab session: Working with 13-F Data10 min
Lab session: Comparing Holding Similarities11 min
Application: network centrality, competition links and stock returns8 min
Application: Using location data to measure home bias to predict returns4 min
3 lectures
Extra materials on Processing Corporate Filings30 min
Additional resources30 min
Additional resources on processing corporate fillings1h 15min
1 exercice pour s'entraîner
Graded Quiz on Processing Corporate Filings
Semaine
4

Semaine 4

7 heures pour terminer

Using Media-Derived Data

7 heures pour terminer
7 vidéos (Total 62 min), 4 lectures, 1 quiz
7 vidéos
Sentiment Analysis6 min
Lab session: Twitter Dataset Introduction10 min
Lab session: Network Visualization4 min
Lab session: Replicating PageRank12 min
Lab session: Applied Sentiment Analysis7 min
Application: Using media to predict financial market variables10 min
4 lectures
Additional resources1 h
Additional resources1h 15min
Extra materials on Using Media-Derived Data1h 10min
Additional resources on using media derived-data2h 30min
1 exercice pour s'entraîner
Graded Quiz on Using Media-Derived Data
4.6

4 avis

Chevron Right

Meilleurs avis pour Python and Machine-Learning for Asset Management with Alternative Data Sets

par KRDec 1st 2019

Different from the other 3 courses but extremely interesting

Enseignants

Image de l'enseignant, Gideon OZIK

Gideon OZIK

Founder and managing partner of MKT MediaStats
Data science and financial economics
Image de l'enseignant, Sean McOwen

Sean McOwen

Quantitative Analyst
Finance

À propos de EDHEC Business School

Founded in 1906, EDHEC is now one of Europe’s top 15 business schools . Based in Lille, Nice, Paris, London and Singapore, and counting over 90 nationalities on its campuses, EDHEC is a fully international school directly connected to the business world. With over 40,000 graduates in 120 countries, it trains committed managers capable of dealing with the challenges of a fast-evolving world. Harnessing its core values of excellence, innovation and entrepreneurial spirit, EDHEC has developed a strategic model founded on research of true practical use to society, businesses and students, and which is particularly evident in the work of EDHEC-Risk Institute and Scientific Beta. The School functions as a genuine laboratory of ideas and plays a pioneering role in the field of digital education via EDHEC Online, the first fully online degree-level training platform. These various components make EDHEC a centre of knowledge, experience and diversity, geared to preparing new generations of managers to excel in a world subject to transformational change. EDHEC in figures: 8,600 students in academic education, 19 degree programmes ranging from bachelor to PhD level, 184 professors and researchers, 11 specialist research centres. ...

À propos du Spécialisation Investment Management with Python and Machine Learning

The Data Science and Machine Learning for Asset Management Specialization has been designed to deliver a broad and comprehensive introduction to modern methods in Investment Management, with a particular emphasis on the use of data science and machine learning techniques to improve investment decisions.By the end of this specialization, you will have acquired the tools required for making sound investment decisions, with an emphasis not only on the foundational theory and underlying concepts, but also on practical applications and implementation. Instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language through a series of dedicated lab sessions....
Investment Management with Python and Machine Learning

Foire Aux Questions

  • Une fois que vous êtes inscrit(e) pour un Certificat, vous pouvez accéder à toutes les vidéos de cours, et à tous les quiz et exercices de programmation (le cas échéant). Vous pouvez soumettre des devoirs à examiner par vos pairs et en examiner vous-même uniquement après le début de votre session. Si vous préférez explorer le cours sans l'acheter, vous ne serez peut-être pas en mesure d'accéder à certains devoirs.

  • Lorsque vous vous inscrivez au cours, vous bénéficiez d'un accès à tous les cours de la Spécialisation, et vous obtenez un Certificat lorsque vous avez réussi. Votre Certificat électronique est alors ajouté à votre page Accomplissements. À partir de cette page, vous pouvez imprimer votre Certificat ou l'ajouter à votre profil LinkedIn. Si vous souhaitez seulement lire et visualiser le contenu du cours, vous pouvez accéder gratuitement au cours en tant qu'auditeur libre.

D'autres questions ? Visitez le Centre d'Aide pour les Etudiants.