Spécialisation Applied Data Science

Commence le Jun 04

Spécialisation Applied Data Science

Get hands-on skills for a Career in Data Science. Learn Python, analyze and visualize data. Apply your skills to data science and machine learning.

À propos de cette Spécialisation

This is an action-packed specialization is for data science enthusiasts who want to acquire practical skills for real world data problems. It appeals to anyone interested in pursuing a career in Data Science, and already has foundational skills (or has completed the Introduction to Applied Data Science specialization). You will learn Python - no prior programming knowledge necessary. You will then learn data visualization and data analysis. Through our guided lectures, labs, and projects you’ll get hands-on experience tackling interesting data problems. Make sure to take this specialization to solidify your Python and data science skills before diving deeper into big data, AI, and deep learning.

Créé par :

courses
4 courses

Suivez l'ordre suggéré ou choisissez le vôtre.

projects
Projets

Conçu pour vous aider à vous exercer et à appliquer les compétences que vous avez acquises.

certificates
Certificats

Mettez en évidence vos nouvelles compétences sur votre CV ou sur LinkedIn.

Vue d'ensemble des projets

Cours
Advanced Specialization.
Designed for those already in the industry.
  1. COURS 1

    Python for Data Science

    Session à venir : Jun 4
    Sous-titres
    English

    À propos du cours

    This introduction to Python will kickstart your learning of Python for data science, as well as programming in general. This beginner-friendly Python course will take you from zero to programming in Python in a matter of hours. Module 1 - Python Basics •
  2. COURS 2

    Data Visualization with Python

    Session à venir : Jun 4
    Engagement
    3 weeks of study, 4-5 hours/week
    Sous-titres
    English

    À propos du cours

    "A picture is worth a thousand words". We are all familiar with this expression. It especially applies when trying to explain the insight obtained from the analysis of increasingly large datasets. Data visualization plays an essential rol
  3. COURS 3

    Data Analysis with Python

    Session à venir : Jun 4
    Engagement
    This course requires approximately two hours a week for six weeks
    Sous-titres
    English

    À propos du cours

    Learn how to analyze data using Python. This course will take you from the basics of Python to exploring many different types of data. You will learn how to prepare data for analysis, perform simple statistical analyses, create meaning
  4. COURS 4

    Applied Data Science Capstone

    Commence le July 2018
    Sous-titres
    English

    À propos du cours

    This capstone project course will give you a taste of what data scientists go through in real life when working with data. You will learn about why data cleaning and munging is an important part of data science and how it occupies more than 80% of a data scientist’s daily work. You will learn about location data and different location data providers, such as Foursquare. You will learn how to make RESTful API calls to the Foursquare API to retrieve data about venues in different neighborhoods around the world. You will also learn how to be creative in situations where data are not readily available by scraping web data and parsing HTML code. You will utilize python and pandas to manipulate data, which will help you help you refine your skills for analyzing data and creating interesting visuals. By the end of the first part of the course you would have compared different neighborhoods and shared your results. Data Scientists also need to be able to work with different kinds of machine learning techniques. In the second part of this course, you will build and apply a machine learning model using the geospatial data from the first part of the project as well as additional data sources, to investigate and attempt to predict neighborhood attributes using techniques like regression, decision trees, clustering, classification, etc. Storytelling and presentation is a very important part of a Data Scientist’s job. By the end of course you would have shared Jupyter notebooks of your implementation and written a detailed report describing your findings. You will also perform peer review of other’s projects.

Créateurs

  • IBM

    Making Smarter Real Industry by Industry

    IBM offers a wide range of technology and consulting services; a broad portfolio of middleware for collaboration, predictive analytics, software development and systems management; and the world's most advanced servers and supercomputers. Utilizing its business consulting, technology and R&D expertise, IBM helps clients become "smarter" as the planet becomes more digitally interconnected. IBM invests more than $6 billion a year in R&D, just completing its 21st year of patent leadership. IBM Research has received recognition beyond any commercial technology research organization and is home to 5 Nobel Laureates, 9 US National Medals of Technology, 5 US National Medals of Science, 6 Turing Awards, and 10 Inductees in US Inventors Hall of Fame.

  • Joseph Santarcangelo

    Joseph Santarcangelo

    Data Scientist at IBM
  • Alex Aklson

    Alex Aklson

    Data Scientist
  • Rav Ahuja

    Rav Ahuja

    Data Science Program Manager

FAQs