Successful Data Science Projects

This is a 2 morning virtual (Zoom & Slack) course held for a small group of circa 10 people mixing scenario solving, new tools and processes and an effective project planning approach that Ian has developed over several years of client-based data science team coaching.
The next course will run on September 26-27.
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This course covers new tools and processes and covers an effective project planning approach that will help you reduce failures and improve deliverable outcomes at work for your data science projects.

It is aimed at anyone who has had failures in their data science projects who’d like to deliver more frequent and more successful projects.

This course is aimed at any Pythonic data scientist who:

  • ● Has had a difficult project delivery and wants more confidence in their process
  • ● Believes that their team could work more efficiently - if only they knew what to change
  • ● Wants to know what a good Definition of Done looks like
  • ● Needs ideas on estimating Costs and Benefits to help plan a project and to sell the benefits (and risks) to colleagues
  • ● Wants to accelerate their own career and leadership potential

During the course we'll:

  • ● Work through scenarios building up some Project Plans (built out of Ian's experience) that define what we know, what we need, risks and milestones so that you could confidently start work on these projects
  • ● Review best practice and the approaches used by successful teams which you can take back to your team
  • ● Review data science tools that'll assist with Exploratory Data Analysis and project derisking that will have an up-front impact on your new projects
  • ● Review the tools and practices used by everyone in the room (you're free to observe if you don't want to participate) to share the good experiences and identify problems that can fixed
  • ● Work through any questions you've brought along from your team
  • ● Use a Slack channel to share results which you can continue to use after the course

After the course you'll:

  • ● Have a Project Plan that you've built-up during the course to take back to apply to your own challenges
  • ● Have a date for a group follow-up call 2 weeks later where we can address any remaining questions you've had when you've applied these techniques back in the office
  • ● Have a "cheat-sheet" with a summary of the main points from the course so you can quickly put them into action back in the office
  • ● Have gained answers to the questions you arrived with, so your personal blockers will be resolved
  • ● Have a plan for new tools and processes to introduce at work to make your team more efficient
  • ● Have access to our Slack channel to continue the conversation with class mates and to download any shared material - you'll also see the discussions from past versions including the post-course tips that were shared by previous students and you can continue to talk with all students through the Slack
  • ● Receive a Certificate of Professional Development
"One of the highlights from Ian’s Successful Data Science Projects course was being introduced to the concept of a specialised project specification document. This provides a systematic framework to directly tackle numerous problems I have experienced when trying to move a project beyond an initial prototyping stage. I have now applied my own tailored specification document at my organisation and it immediately surfaced critical questions and issues that otherwise would not have been realised for months."
- Thomas Brown, Data Scientist at

"After attending the course I can identify and communicate to the project team and client the uncertainties of the project efficiently. I am using the techniques covered on the course to write project initiation documents and put in place the necessary processes to reduce uncertainty. The course was very engaging and I was very happy to learn from Ian's experience to ensure a successful delivery on all future projects."
- Dani Papamaximou, Data Scientist at Arcadia
Get in contact with Ian
If you’d like to discuss how Ian can help your team, get in contact by emailing Ian[at]
  • Read my book

    Oreilly High Performance Python by Micha Gorelick & Ian Ozsvald
    Oreilly High Performance Python by Micha Gorelick & Ian Ozsvald