1-on-1 Mentoring

Career success requires more than education and willingness to work. Many successful people have benefited from having a mentor, a guide to the field, who can answer questions, point out opportunities, and smooth the way for a newcomer.
The 1-on-1 mentorship is hyper-personalized and hence it is completely “mentee-driven”. The 1-on-1 session template will help you to plan the agenda along with a template to maintain a weekly log of your progress and a workbook to keep track of your goals. This is the single source of truth for your mentor to understand where you are.
Here is the link to .
Guidelines
Please come to the mentoring sessions prepared. You must have done some work on Glabs and spent time learning before coming into the session to make the optimum use of the mentoring session.
Think through what you wish to discuss with the mentor relevant to your data science learning and career. The agenda themes identified below will help you in framing your thoughts.
Frame your doubts properly. Show the mentor that you have put in your effort and genuinely asking doubts.
Wrong doubt: What is Data Science?
Right doubt: I have read about data science and I am unable to understand how to check if data science is applicable. Could you point me to the right resource or explain in brief?
Don’t ask mentor for help with the glabs assignments during learning. If you are stuck, the GA slack workspace is the right place. Use these sessions to show your projects, resume, etc and get feedback from the mentor.
We are here to provide all the support, environment and community to help you succeed. Once you must put in your hard work and effort (and this is the most imp ingredient for success), you are bound to succeed.

Schedule : Thrice a month for 30 minutes.
Total Sessions : 24 sessions over the period of 8 months
Mentoring Journey
0
Search
Month
Theme
Expectations
1
Month 1
Python Programming
Get comfortable with Programming with Python
Work on multiple projects to get used to programming
Get your projects evaluated as well as get feedback to improve from your Mrntor
2
Month 2
Math and Stats
Get comfortable with the basics of Math and Stats require to understand ML
Get your doubts cleared in every mentor session
Complete chapter and sprint end projects and get them evaluated by your mentor
3
Month 3
Machine Learning
Understand the basic processlike EDA, Data Preprocessing and Model building to get a ML solution
Clear your doubts as well as get various tips and tricks to build a ML solution
Complete chapter and sprint end projects and get them evaluated by your mentor
4
Month 4
Advanced Machine Learning
Understand advanced ML techniques like hyperparameter tuning, Feature Selection and various algorithms
Discuss with your mentors on showcasing your projects done on Github
5
Month 5
End to end problem solving
Understand about end to end problem solving
Get feedback on your end to end solutions from the mentor
Discuss with your mentor on improving your hackathon outputs
6
Month 6
Resume Building, Portfolio projects
Build an appropriate resume, end to end portfolio projects
Get your job profile reviewed by your mentor
7
Month 7
Interview Process
Get prepared for interview process and build out a job search strategy
Discuss your interview expectations/experience with the mentor
Get advice on improving your interveiw outcome with mentor
8
Month 8
Fine Tuning your profile
Discuss your strengths and weakness with the mentors
Build an improvement strategy
There are no rows in this table
Want to print your doc?
This is not the way.
Try clicking the ⋯ next to your doc name or using a keyboard shortcut (
CtrlP
) instead.