Guidance to prepare and learn SQL, SAS, Python, R

r
sql
sas
python

#1

Hi All,

Myself has got work experience in financial sector for over 11 years in various captive units, however for a long term plan i would like to shift to my career in analytics domain. Kindly guide me how to start in order to learn and build up knowledge of various languages such as SAS, SQL, Python etc. Kindly suggest me where to start including going through required statics chapters, basic coding etc.

Appreciate your valuable advice in this matter.


#2

Tips to learn SQL

Tip 1 : Learn Basic ideas hypothetically :

You need to take in the SQL ideas hypothetically. You can utilize diverse websites to take in the SQL ideas effectively.

Tip 2 : Do the down to earth of Basic SQL:

Simply realizing the things hypothetically won’t work.User needs to do the idea basically. The most ideal approach to learn SQL is to get hands on understanding of SQL with utilizing its vital ideas.

Tip 3 : Choosing Database Management System:

To begin learning with SQL client needs to pick the database the board framework. This is most vital advance. There are such huge numbers of good database the board frameworks and its free forms are additionally accessible. Oracle,SQL Server are the most utilized database the board frameworks.

Tip 4 : Stick with just a single blog to learn SQL :

I would propose you to stay with one blog to learn SQL. On the off chance that you allude different web journals you get befuddle about the correct learning.

Tip 5 : Complete fundamental SQL ideas and Jump to complex SQL Queries :

Subsequent to picking the Database Management System client needs to finish the fundamental SQL ideas and bounce to learn complex sql queries.I might want to give you some essential instances of SQL which encourages the client to begin with SQL (I am utilizing database the executives framework as ‘Prophet’)

Tips to learn R programming

To learn R programming, begin with R programming course in coursera by Roger Peng. It acquaints you with the essentials of the R programming. At that point, to apply it, begin applying it on an informational index. Your Home for Data Science has an instructional exercise in how to do break down information. It utilizes Titanic informational index. You can likewise take in some machine learning essentials there.

I recommend you use R Studio as the apparatus. It makes learning R a lot less demanding. In the event that you have enough time, attempt coursera seminars on information science by John Hopkins college, or by Harvard college at EdX. DataCamp: Learn R, Python and Data Science Online additionally gives instructional exercises on R programming and Python.

Tips to learn Python

Make It Stick

Tip 1: Code Everyday

Tip 2: Write It Out

Tip 3: Go Interactive!

Tip 4: Take Breaks

Tip 5: Become a Bug Bounty Hunter

Make It Collaborative

Tip 6: Surround Yourself With Others Who Are Learning

Tip 7: Teach

Tip 8: Pair Program

Tip 9: Ask “Great” Questions

Make Something

Tip 10: Build Something, Anything

Tip 11: Contribute to Open Source

Go Forth and Learn!

Tips to learn SAS

Get the SAS/IML Software. In the event that your work environment does not permit the SAS/IML item, you can download the free SAS University Edition onto your workstation for learning SAS/IML. Regardless of whether SAS/IML programming is accessible at work, you should need to download the University Edition in the event that you intend to learn and practice during the evening or on ends of the week.

Work through the “Beginning” section of the book Statistical Programming with SAS/IML Software. The part is accessible as a free portion from the book’s Web page. Notice that I say “work through,” not “read.” Run the projects as you read. Change the numbers in the models. On the off chance that you need a more extended presentation, read Wicklin (2013) “Beginning with the SAS/IML Language.”

Work through the initial six parts of the SAS/IML User’s Guide. A couple of years back I reexamined this documentation to make it increasingly decipherable, particularly the segments about perusing and composing information.

Download the SAS/IML tip sheets. By keeping a tip sheet around your work area, you can undoubtedly help yourself to remember the grammar for normal SAS/IML proclamations and capacities.

Buy in to The DO Loop blog. Most Mondays I blog about basic points that don’t require propelled programming abilities. I additionally examine DATA step programs, factual designs, and SAS/STAT strategies. I’ve composed in excess of 100 blog entries that are labeled as “Beginning.”

Program, program, program. The best approach to take in any programming dialect is to begin composing programs in that dialect. When I was a college educator, I used to tell my understudies “Math isn’t an onlooker sport.” Programming is comparable: In request to show signs of improvement at programming, you have to work on programming. A large number of the past tips furnished you with pre-composed projects that you can alter and expand. The paper “Rediscovering SAS/IML Software: Modern Data Analysis for the Practicing Statistician” incorporates middle of the road level precedents that show the intensity of the SAS/IML dialect.

Utilize the SAS/IML Support Community. When you begin composing programs, you will definitely have questions. The SAS/IML Support Community is a talk gathering where you can post code and request help. As you gain involvement, have a go at noting questions posted by others!

Consider productivity. A contrast between a beginner software engineer and an accomplished developer is that the accomplished developer can compose proficient projects. In a grid vector dialect, for example, SAS/IML, that implies vectorizing programs: utilizing framework activities rather than circles over factors and perceptions. Many programming tips and strategies in the initial four parts of Statistical Programming with SAS/IML Software manage effectiveness issues. As you gain understanding, consider the productivity precedents and vectorization models in my blog.

Utilize the SAS/IML Studio programming interface. I am progressively profitable when I use SAS/IML Studio than when I use PROC IML in the SAS Windowing condition (show administrator). I like the shading coded program manager and the capacity to create and run numerous SAS/IML programs all the while. I like the investigating highlights and the progressively connected illustrations are frequently valuable for understanding connections in information.

Utilize the SAS/IML File Exchange. The SAS/IML File Exchange is a Web webpage where you can scan for helpful projects to utilize, think about, or alter. The trade is similar to those “Leave a penny; take a penny” bowls at money registers. On the off chance that you have composed a cool program, contribute it with the goal that others can utilize it. On the off chance that you require a capacity that plays out a specific investigation, download it from the website. The site propelled in mid-2014, so we require commitments from numerous SAS/IML software engineers before the site will wind up valuable.

Hope you got proper answer…please follow all tips
All The Best!!


#3

@tupai1982

First tip - don’t go after learning all the languages. All you need is good knowledge of one language. I would pick either R or Python.

You can check out this complete learning path we had created at the start of the year: https://trainings.analyticsvidhya.com/courses/course-v1:AnalyticsVidhya+Python-Final-Jan-Feb+Python-Session-1/info

We will be refreshing it shortly - but the journey would remain similar, so you can start quickly.

Hope this helps.

Regards,
Kunal