LinkedIn (Do and Don’t)
In this article, you will discover very important Do’s and Don’ts of LinkedIn etiquette and the mistakes you absolutely must avoid making. These Do’s and Don’t is suggested by LinkedIn itself.
LinkedIn Etiquette: 10 Things You Must Do
1. Personalize Connection Requests
2. Send a Welcome Message
3. Respond Promptly…[Read more]
Tips on using linkedin
How to Use LinkedIn to Find a Job – Or Have a Job Find You
What do Microsoft, eBay, Netflix, and Target have in common? All these companies (and many more) have used LinkedIn to recruit candidates for employment. LinkedIn is an online directory of individual professionals and organizations. Individuals use LinkedIn for…[Read more]
Tips to write a powerful resume
Write a powerful resume
Your resume discloses a lot more about personal, professional details of you, it reveals,
How you view yourself.
How well you can present yourself.
How much you love your success.
How positive and energetic you are for achieving success.
How creative you are.
How well you can sell…[Read more]
Here are the links compiled by us where you can find contents, training and tutorials for
1. The vogella GmbH is a German company based in Hamburg. It offers services such as
consulting, development, development support and training in the Eclipse, Android and
Git. They provide free online tutorials in Java, Eclipse, Web, Git and A…[Read more]
"Non-Techinical questions asked in interview".
1. Why are leaving your current position?
2. What do you like or dislike the most about your current comapany?
3. How do you handle pressure?
4. What are your strengths and weakness? For this we have post from sakshi
in our forum..so please dont concentrate on this question
5. Where do you see…[Read more]
Learn Data Analytics before diving deep into Data Science
Is it true that to become a data scientist you master the following: statistics, linear
algebra, calculus, programming, databases, distributed computing, machine learning,
visualization, experimental design, clustering, deep learning, natural language
processing, and more???
The answer…[Read more]
What’s the trade-off between bias and variance?
What is the difference between supervised and unsupervised machine learning?
How is KNN different from k-means clustering?
Explain how a ROC curve works.
Define precision and recall.
Why is “Naive” Bayes naive?
What is data science?
How does data science compare to software engineering?
How does…[Read more]