This blog is written considering people who have elementary knowledge on personal finance but enthusiastic about starting fresh towards the rewarding journey of investment. They should try to follow below simple steps to begin with, 1.First analyze your income and expenses
thoroughly, not only your big-ticket expenses like EMI, but even minute details
like laundry expenses which will give you realistic picture how well are you managing your income and expenditure.
2.Create an emergency fund which should be no less
than 3 months’ of your monthly income. This will act as a primary cushion for
unemployment or unavoidable circumstances.
3.Buy Family floater plan for you and your
dependents even if you have an insurance from your company. This will be very
helpful when you are out of job or even for buying individual coverage at a
later stage of life.
4.Buy a term insurance plan for your dependent to
protect your family from any hardship in future in your absence.
The enthusiasm for entrepreneurship is ever growing. However though it is debatable whether formal education really is a prerequisite to be an entrepreneur, we can at least say there is no harm if you start your entrepreneurial journey with some formal education about business.
There are plethora of choices exist now for entrepreneurship courses, I am highlighting few of those which have created their marks already. SIBM 2 Year MBA in Innovation and Entrepreneurship – This is a formal full time MBA course taught in the same prestigious SIBM Pune campus. Aspirants have to appear for CAT, however general cutoff for this course is much lower (65% - 75%) compared to SIBM Pune’s flagship MBA BM course where cut off is around 98%. Course fee is around 15 lakhs and no placement is provided to the students to encourage entrepreneurship. TISS 2 Year MA in Social Entrepreneurship – This is one of the most sought-after full time course on Social Entrepreneurship started by one of the most resp…
It is very easy to become confused when you start your data
science journey. However the problem is not dearth of study materials, but
having too many of them! It is almost impossible to find the best in the heap
and becoming frustrated is natural. As I had started my data science journey 6 months back, I am
providing list of only three best resources in each area which really helped me
a lot for steady progress. I hope it will help you also to declutter your
confusions and come up with an actionable plan.
A.Books: 1.Python Machine Learning by Sebastian Raschke 2.Think Stats – Exploratory Data Analysis in
Python – Allen B Downey 3.Introduction to Statistical Learning – by Gareth
James (for R)
B.Courses: 1.CS109 – Data Science by Harvard (For more
advanced, CS229 – ML by Stanford) 2.Machine Learning by Stanford University – Coursera 3.Machine Learning A-Z, Hand on Python & R in
2.kaggle.com (this is also an exvellent source of pratice data s…