Learn Project Management at These 57 Project Management Bootcamps

• Meeting new people with different backgrounds and ways of thinking, with a common interest in moving from academia to a career in data science
• Connecting with the broader network of alumni, including panel evenings with course alumni in which one can learn about both finding jobs, but also the longer-term career paths that data scientists travel
• Working alongside project partners from commercial companies, learning how to craft insights that solve real-world problems and offer value to potential clients
• Technical mentorship that goes beyond just coding to offer valuable perspectives on the role of data science within organisations
• Time and space to learn about new tools in data science and understand how the strengths and limitations of different quantitative methods relate to business needs
• Experience working collaboratively using industry-relevant tools (GitHub, Slack, AWS) and Agile practices

• longer duration of the course (4.5 months compared to 3);
• broader program and more workload on the course (Beginner and Middle level topics, 2 two-hour lectures/practices on weekdays + 4-hour practices every Saturday as opposed to only Beginner level topics and 2 meetings of 2 hours);
• choice of your own topic for the graduation project (instead of the whole group creating different variants for a real client based on a specific task, which the client paid for, to have the graduates choose his task, as it happens at Projector);
• not the least reason was the work of the sales manager, who provided me with the level of service that was not in the first failed option and the usual communication with the sales manager from Projector, whose interest in getting me on the course was not felt.

• support from the academy throughout the course;
• the teacher! Her level of knowledge, ability to explain, interest in the success of students, willingness to help with every question that arises;
• own LMS, where each lesson has homework, several video lessons, and a lot of quality textual information taken from various well-known and not very reliable sources;
• slight changes in the program or individual homework at the choice of the teacher — it was done to give us only the necessary knowledge, based on real cases in practice;
• a well-thought-out process of defending the graduation project and the ability to defend it in English;
• friendly community within the group and overall at the academy;
• the presence of educational events, workshops, and free career counseling for each student;
• cool merch for all students;
• the ability to split the payment for the course into a convenient number of parts.

• somewhat outdated links to some information;
• in general, the order of video lectures sometimes confused, and sometimes there was a feeling that the videos were taken from previous versions of this course;
• the teacher's answers to questions about the course/graduation project, even within the allocated time, were long and postponed to another day, despite her online presence;
• minor errors in tests and in some places not very well-thought-out UI/UX in LMS.

The application process can be daunting and intimidating, however, each step has its reasons. This makes each cohort learn and progress in a homogeneous pace, which is key to a successful completion of the TDI. 

I was part of the D.C 2017 winter cohort and the 8 weeks were key to position myself as a Data Scientist in the industry. You share and work collaboratively with the rest of the cohort, making it invaluable because you are not only learning from the diverse curriculum but also from your peers. At the end of the day, Data Science is both a Science and an Art, so different perspectives and approaches to problem-solving definitely enhance your skillset. 

Additionally, there is a focus on soft skills, from getting your resume up to speed to effective communication. Each week there are dedicated sessions on how to tackle interview questions, how to sell yourself, and how to navigate opportunely the recruiting process, complementing TDI's rigorous technical curriculum. 

Going to the TDI was not only enriching but also enjoyable. You come out of the program with a powerful network of top-notch data scientist, a second to none skillset and the right toolkit to navigate the corporate world.