Boot Camps

Driving growth in crowded markets is becoming more and more challenging. And that too with COVID-19 affecting each sector across the globe, it's going to be a lot difficult and different to make a mark in the market and stand out from the rest.

To address these challenges, Growth Folks and SEMrush bring you an exclusive webinar.

Date: 22nd April 2020
Time: 8:00 pm IST

In this session, Anna Lebedeva, Head of Growth Marketing at SEMrush, will talk about effective online visibility and what questions modern marketers should focus on in this new customer-focused age. She will show a real-live case of a brand that changed their marketing strategy to become a part of customer context which resulted in 2x revenue increase.
Register now →
About the Speaker:

Anna Lebedeva is currently working as the Head of Growth Marketing at SEMrush. Her experience covers SaaS, tech and media industries with comprehensive knowledge of the global tech, media and marketing landscape. She has a passion for digital marketing, new technologies, and media.
Olga Burnaeva
See you there,
Olga Burnaeva
Online Marketing Specialist

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ACM-IMS Gathering in San Francisco to Focus on Deep Learning, Ethics, Fairness and

the Future of Data Science

New York, NY, May 20, 2019 – Computing and statistics underpin the rapid emergence of Data Science as a pivotal discipline today. As the two key professional organizations in these areas, the Association for Computing Machinery (ACM) and the Institute of Mathematical Statistics (IMS) have organized the ACM-IMS Interdisciplinary Summit on the Foundations of Data Science to be held June 15, 2019 at the Palace Hotel in San Francisco. This one-day event will bring together distinguished speakers and panelists to address topics such as deep learning, reinforcement learning, fairness, ethics, and the future of data science.



Keynote Speakers:

Emmanuel Candès, Professor of Mathematics and Statistics at Stanford University

(keynote title tbd)


Jeffrey Dean, Google Senior Fellow and SVP, Research and Health

“Deep Learning for Tackling Real-World Problems”


Daphne Koller, CEO and Founder, insitro

“Human Biology through the Lens of Data”


Panel Discussions:

Deep Learning, Reinforcement Learning, and Role of Methods in Data Science

Moderator: Joseph Gonzalez (University of California, Berkeley)
: Shirley Ho (Flatiron Institute), Sham Kakade (University of Washington), Suchi Saria (Johns Hopkins University) and Manuela Veloso (J.P. Morgan AI Research and Carnegie Mellon University)


Robustness and Stability in Data Science

Moderator: Ryan Tibshirani (Carnegie Mellon University)

Panelists: Aleksander Madry (MIT), Xiao-Li Meng (Harvard University), Richard J. Samworth (University of Cambridge and The Alan Turing Institute), and Bin Yu (University of California, Berkeley)

Fairness and Ethics in Data Science

Moderator: Yannis Ioannidis (Athena Research Center) 
: Joaquin Quiñonero Candela (Facebook), Alexandra Chouldechova (Carnegie Mellon University), Andrew Gelman (Columbia University) and Kristian Lum (Human Rights Data Analysis Group)

Future of Data Science

Co-Moderators: David Madigan (Columbia University), Jeanette Wing (Columbia University)  

Panelists: Michael I. Jordan (University of California, Berkeley), Adrian Smith (The Alan Turing Institute)

Steering Committee:  Jeannette Wing (Event Co-Chair), David Madigan (Event Co-Chair), Magdalena Balazinska, Joseph Gonzalez, Chris Holmes, Yannis Ioannidis, Ryan Tibshirani, and Daniela Witten

MEDIA REGISTRATION:  Contact Jim Ormond at This email address is being protected from spambots. You need JavaScript enabled to view it.

About ACM

ACM, the Association for Computing Machinery, is the premier global community of computing professionals and students with nearly 100,000 members in more than 170 countries interacting with more than 2 million computing professionals worldwide.

About IMS

IMS, the Institute of Mathematical Statistics, is the leading organization fostering the development and dissemination of the theory and applications of statistics.

The swelling demand for data scientists coupled with the evident skills gap has implications for the global economy as well as the tech industry. What’s causing it, and what can be done to address it?

In 2017, Burning Glass TechnologiesBusiness-Higher Education Forum and IBM came together to produce a report on the demand for data science skills. Here are some of the highlights:

  • It forecast that the number of jobs for all data openings will increase by 364,000 by 2020, bringing the total to 2,727,000
  • The fastest-growing roles are Data Scientists and Advanced Analysts, which are projected to see demand spike by 28% by 2020
  • DSA jobs remain open for 45 days— five days longer than the market average.
  • The difficulty employers have filling DSA roles drives up salaries, and relative to other jobs, DSA jobs pay quite well. On average, they advertise an annual salary of $80,265—a premium of $8,736 relative to all bachelor’s and graduate-level jobs
  • Compounding the skill shortage is the hybrid nature of many DSA jobs, which require a mix of disparate analytical skills and domain-specific expertise that may be difficult to develop in traditional training programs
  • Machine learning, big data, and data science skills are the most challenging to recruit for and potentially can create the greatest disruption to ongoing product development and go-to-market strategies if not filled

According to a LinkedIn report, the top Data Science jobs in 2018 comprise – Data Scientist, Data Security Administrator, Data Analyst, Business Intelligence Analyst, and Network Administrator.

So, here are some questions for you:

What kind of Data Science Professional are you?

 What are you going to do to get ready to ride the ‘data’ rush wave?

To get you started in this area, IBM has developed the Data Science Professional Certificate on Coursera. It consists of 9 courses that are intended to arm you with latest job-ready skills and techniques in Data Science. The courses cover variety of data science topics including: open source tools and libraries, methodologies, Python, databases and SQL, data visualization, data analysis, and machine learning. You will practice hands-on in the IBM Cloud (at no additional cost) using real data science tools and real-world data sets.

The courses in the Data Science Professional Certificate include:

  1. What is Data Science
  2. Tools for Data Science
  3. Data Science Methodology
  4. Python for Data Science
  5. Databases and SQL for Data Science
  6. Data Visualization with Python
  7. Data Analysis with Python
  8. Machine Learning with Python
  9. Applied Data Science Capstone

Each of the courses also gives you an opportunity to earn an IBM open badge, which allows you to build your digital resume and makes you discoverable (by opting in) to potential employers. Additionally, for a limited time, this course is available at an attractive price of $39 per month! Learn more about exactly what’s covered in the courses here

Read Source Article IBM

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Here are the few links regarding IBM Data Science Professional Certificate on Coursera

#AI #DataScience #courses #Certificate #IBM #Coursera

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