Predictive Modeling using SAS & R Online Training

The next Instructor-led online training batch will commence on October 8, 2017. We are offering courses on SAS , R and Predictive Modeling. In this program you will get an access to live lectures plus recorded videos from any part of the world via web conference mode. Also you can chat or even ask their questions verbally over the VoIP in real time to get their doubts cleared.

1. Practical SAS Programming - Learning SAS by Case Studies
2. Predictive Modeling with SAS - Modeling with Hands-on Examples plus Domain Knowledge
3. Data Science using R - Practical Data Science Course (Incld. R Programming, Data Science and Domain Knowledge)


Batch : 8th October, Sunday     Mode : Live Instructor-led

It is an interactive training program. Learners will get an access to live lectures via live webinar mode and can chat or even ask their questions verbally over the VoIP in real time to get their doubts cleared. Also you can go through video recording if you miss a class.

If you do not like our training, you can ask for 100% course fees refund after your first live session. No question asked refund policy!

These are weekend programmes comprising 100-130 hours. Classes will be held on every Saturday and Sunday The course duration is as follows -

1. Practical SAS Programming - 100 hours (At least 50 hours live training + 5 hours video based training + ~60 hours of Practice and Self Study)
2. Predictive Modeling with SAS - 100 hours (Includes hours of Video based training and Practice and Self Study)
3. Data Science with R - 120 hours (At least 60 hours live training + 7 hours video based training + ~80 hours of Practice and Self Study)

All classes will be scheduled on weekend but not at the same time. It'll be one by one. For example if class A gets over at 5. Next class will start at 6.

Here are some of the features of ListenData that makes us better than other training institutes.

1. Explain Advanced Statistical and Machine Learning Algorithms in Simple English. We make classes more logical and understandable than just telling concepts.
2. Practical Application of Techniques using Real-world Datasets. No sample or cleaned dataset.
3. Domain Knowledge - It is the most important element of a predictive modeling project. People who lack in domain knowledge find it difficult to crack interviews in spite of having knowledge of predictive modeling.
4. Hands-on Model Development and Validation
5. Strategies to implement predictive model
6. New algorithms to solve problems efficiently
7. Explain complex topics via visual lessons

These courses are ideal for candidates who want to make a career in analytics.

1. Any candidate pursuing graduation / post graduation or already graduate can apply for this course. No particular specialization is required prior to applying for these courses. You can be from any educational background like Engineering, Economics, Statistics, Mathematics, Commerce, Business Management, Operational Research etc.
2. Anyone who is planning a career shift to analytics. It does not matter if you are a network engineer or financial analyst. You can go ahead with these courses as they do not require any prior knowledge of programming or statistics.

Let's be honest! It's a universal fact that no college or training institute can provide 100% job guarantee. If they are claiming 100% job guarantee, they are luring learners by false promises. Even IITs do not hit 100% score. Some Facts - Only 66% of IITians landed a job offer via campus recruitment in 2016-17, as against 79% in 2015-16 and 78% in 2014-15, according to HRD ministry.

Let me list down the common reasons why people don't get jobs in analytics industry even after completing training from some colleges / institutes -

1. No hands-on experience
2. No domain knowledge
3. No theoretical knowledge of statistical concepts
4. Poor analytical skill

The objective of this program is to cover the above first three points in detail. In addition we provide job placement assistance to all students. We will keep you informed about current openings in analytics industry. We are in constant contact with job consultancy firms and a solid network of analytics professionals.

I have been working in SAS for close to 7 years and worked with 4 organizations (Instability in career! :D ). Whenever I look for a job change, I do not see any decline of SAS jobs in the market. Don't trust me, go to job portals and search 'SAS'! List of Companies using SAS It is a big hit in banks, insurance, telecom and pharmaceutical companies. SAS is still a world leader in advanced analytics and has over 40,000 customers worldwide. It has been tagged 'leader' consistently in advanced analytics platform as per Gartner 2015 and 2016 reports. It is one of the most sought after skill in job market. Learning SAS will help you to scale up your skills, which in turns leads to boost your career.

At the same time, R has gained popularity. It is a language of choice for data scientists. It makes advanced statistical techniques and machine learning algorithms easy to implement. It is being used as a primary tool in IT, ecommerce, startups, HR, service and product based companies and secondary tool in banks, insurance and telecom companies. List of Companies using R

Final Comment - You should not get into language wars and should focus on learning both the languages as jobs are evolving very fast. Companies prefer candidates who know both SAS & R.

Every class is recorded. We will provide you recording of every session.

Yes, these courses are designed to keep in mind the needs of non-programmers/non-statisticians. Only prerequisite is hard work and zeal for learning.

100% refundable. Incase you want to opt out of the course for any reason, you can ask for 100% refund within 7 days of registration. If you want to continue, it would be automatically adjusted on total fees. In other words, you pay $15 (Rs 1000) less of the amount of total fees.

Deepanshu founded ListenData with a simple objective - Make analytics easy to understand and follow. He has close to 7 years of experience in data science and predictive modeling. He has worked with companies like Aon, Cognizant, Genpact, RBS. He has handled global clients in various domains like retail and commercial banking, Telecom, HR and Automotive. He has worked extensively in various data science projects such as Customer Attrition, Customer Lifetime Value Model, Propensity Model, Opinion / Sentiment Mining, Geo Analytics, Credit risk scorecard, Portfolio Optimization, Pricing Analytics, Cross sell/Up sell campaign models, Survey Analytics, Customer Segmentation, Market Benchmarking, Employee Attrition, Employee Engagement etc.

Please feel free to write me at deepanshu.bhalla@outlook.com OR Join me on linkedin