The course is offered online and on-site.
Become a data analyst. Learn to load, clean, explore and extract valuable insights from a wide range of datasets as well as cultivate tools and languages such as Python, SQL and Tableau. Develop the statistical knowledge to conduct rigorous analyses, transform data into astonishing visualizations, and present your findings in thoughtful, focused and engaging presentations.
Who is Ironhack's Data Analytics Part-Time for?
Need to enrich your resume with hard-hitting projects? Trying to develop real-world skills that are valued in the data industry? Our bootcamp will help you secure your spot in the data industry.
Has your career hit a bottleneck? Switch to the data world! Every single industry is beginning to incorporate — now is the moment for you to leverage your current expertise and evolve your career! Enter the data industry with this course, which has been specifically designed to teach you the necessary knowledge and skills.
Looking to break away from the pack? Read into the secret knowledge of analytics by developing cross-disciplinary expertise in data. With this course, not only can you propel your career forward, you can also take it in a new direction.
Discover how data can give your company that extra edge against the competition in a world that’s accelerating every minute. This course offers you a deep understanding of the current data tech and practices that’ll be essential to growing your company.
Data Analytics Course Syllabus & Structure
During your first 60 hours as an official Ironhack Data Analytics student, you will be laying the foundation for success in . During the prework phase you will:
learn the fundamentals of command line, Git, Python, MySQL and statistical analysis,
familiarize yourself with the basics of programming and statistics and
connect with your peers and expert academic staff by utilizing our Slack channel.
Once you’ve completed the prep materials and synced up with your class, you’ll be ready to dive into the course!
Module 1: Introduction to and Python
The first five weeks will introduce you and your classmates to the world of data analytics. Then you will establish your development environment for the classroom as you settle into our tightknit data community. Topics include:
Introductions to data wrangling/cleaning.
APIs and web scraping.
Intermediate levels of Git, SQL and Python.
Week six through eight call for your first project as an apprentice data analyst! Apply your new Python skills by conducting data analysis with real datasets.
Module 2: Advanced
In weeks nine through thirteen, you’ll take a deeper look into the mathematics behind data analytics. Topics include:
Utilizing Python to understand inferential statistics and probability.
Incorporating Python into the fundamentals of business intelligence.
Learning story-telling techniques in order to visualize your data and insights in presentations.
Week fourteen will mark the start of your second project: a complete data analysis. This will be constructed from data that you will have processed, cleaned and visualized from real datasets!
Module 3: Get a handle on the fundamentals of machine learning
The final module will introduce you to the fundamentals of machine learning in weeks 17 through 21. We’ll start things off by teaching you to understand the machine workflow, and the lessons will only expand from there. Topics include:
Both supervised and unsupervised learning
The essentials of popular machine learning algorithms.
Building, training and evaluating models with the Scikit-Learn machine learning library.
The last three weeks of this module and course, you will face your final and most challenging task: building an end-to-end machine learning project. You will process a dataset, extract features, train a model, and use that model to make predictions on new data. When your project is complete, you will compete alongside your fellow students in our Hackshow.