DataTalks.Club

By DataTalks.ClubTechnology

DataTalks.Club episodes

April 09, 2021Transitioning from Project Management to Data Science - Ksenia Legostay
We talked about:
Knesia’s background

Data analytics vs data science

Skills needed for data analytics and data science

Benefits of getting a masters degree

Useful online courses

How project management background can be helpful for the career transition

Which skills do PMs need to become data analysts?

Going from working with spreadsheets to working with python

Kaggle

Productionizing machine learning models

Getting experience while studying

Looking for a job

Gap between theory and practice

Learning plan for transitioning

Last tips and getting involved in projects

Links:
Notes prepared by Ksenia with all the info: https://www.notion.so/ksenialeg/DataTalks-Club-7597e55f476040a5921db58d48cf718f

Join DataTalks.Club: https://datatalks.club/slack.html
1 hr 4 min
April 02, 2021Building Online Tech Communities - Demetrios Brinkmann
We talked about:
Demetrious’ background and starting the MLOps community

Growing MLOps community

Community moderations and dealing with problems

Becoming a community and connecting with people

Feeling belonged

Managing a community as an introvert

Keeping communities active

Doing custdev and talking to users

Random coffee and meeting with community members

Organizing community activities

Is community a business?

Five steps for starting a community in 2021

Shameless plug from Demetrious

Links:
https://mlops.community/

Join DataTalks.Club: https://datatalks.club/slack.html
1 hr 14 min
March 26, 2021DataOps 101 - Lars Albertsson
We talked about:
Lars’ career

Doing DataOps before it existed

What is DataOps

Data platform

Main components of the data platform and tools to implement it

Books about functional programming principles

Batch vs Streaming

Maturity levels

Building self-service tools

MLOps vs DataOps

Data Mesh

Keeping track of transformations

Lake house

Links:
https://www.scling.com/reading-list/

https://www.scling.com/presentations/

Join DataTalks.Club: https://datatalks.club/slack.html
1 hr 10 min
March 19, 2021The Essentials of Public Speaking for Career in Data Science - Ben Taylor
We talked about:
Ben’s background

AI evangelism

Ben’s first experiences speaking in public

Becoming a great speaker

Key Takeaways and Call to Action

Making a good introduction

Being Remembered

Writing a talk proposal for conferences

Landing a keynote

Good topics to start talks on

Pitching a solution talk to meetup organizers

Top public speaking skill to acquire

Book recommendations

Join DataTalks.Club: https://datatalks.club/slack.html
1 hr 9 min
March 12, 2021New Roles and Key Skills to Monetize Machine Learning - Vin Vashishta
We discussed monetization roles and the capabilities people need to move into those roles.
The key roles are ML Researcher, ML Architect, and ML Product Manager.

We talked about:
Vin's career journey
What does it mean to "monetize machine learning"

Important monetization metrics

Who should we have on the team to make a project successful

Machine Learning Researcher (applied and scientist) - background, responsibilities, and needed skills

Developing new categories

The best recipe for a startup: angry users + data scientists

What research actually is

ML Product Manager - background, responsibilities, and needed skills

How product managers can actually manage all their responsibilities (and they have a lot of them!)

ML Architect - background, responsibilities, and needed skills

Path to becoming an architect

How should we change education to make it more effective

Important product metrics

And more!

Links:
https://twitter.com/v_vashishta

https://linkedin.com/in/vineetvashishta

https://databyvsquared.com/

Join DataTalks.Club: https://datatalks.club/slack.html
1 hr 20 min
March 05, 2021Personal Branding - Admond Lee Kin Lim
We talked about:
Admond's career journey

What is personal brand

How Admond started being active online

Publishing on medium and LinkedIn

Idea generation process and tools

Other platforms

Podcasts

Offline presence

1x1 meetings

Speaking on conferences

Having confidence to publish

Selling online courses

Personal values

Admond's course
And many other things
Links:
https://twitter.com/admond1994

https://linkedin.com/in/admond1994

https://buzzsumo.com

https://feedly.com/

https://lunchclub.com/

https://thelead.io/data-scientist-personal-brand-toolkit?utm_medium=instructor&utm_source=admond

Join DataTalks.Club: https://datatalks.club/slack.html
1 hr 14 min
February 26, 2021The ABC’s of Data Science - Danny Ma
Did you know that there are 3 types different types of data scientists? A for analyst, B for builder, and C for consultant - we discuss the key differences between each one and some learning strategies you can use to become A, B, or C.

We talked about:
Inspirations for memes

Danny's background and career journey

The ABCs of data science - the story behind the idea

Data scientist type A - Analyst

Skills, responsibilities, and background for type A

Transitioning from data analytics to type A data scientist (that's the path Danny took)

How can we become more curious?

Data scientist B - Builder

Responsibilities and background for type B

Transitioning from type A to type B

Most important skills for type B

Why you have to learn more about cloud

Data scientist type C - consultant

Skills, responsibilities, and background for type C

Growing into the C type

Ideal data science team

Important business metrics

Getting a job - easier as type A or type B?

Looking for a job without experience

Two approaches for job search: "apply everywhere" and "apply nowhere"

Are bootcamps useful?

Learning path to becoming a data scientist

Danny's data apprenticeship program and "Serious SQL" course

Why SQL is the most important skill

R vs Python

Importance of Masters and PhD

Links:
Danny's profile on LinkedIn: https://linkedin.com/in/datawithdanny

Danny's course: https://datawithdanny.com/

Trailer: https://www.linkedin.com/posts/datawithdanny_datascientist-data-activity-6767988552811847680-GzUK/

Technical debt paper: https://proceedings.neurips.cc/paper/2015/hash/86df7dcfd896fcaf2674f757a2463eba-Abstract.html

Join DataTalks.Club: https://datatalks.club/slack.html
1 hr 26 min
February 19, 2021Translating ML Predictions Into Better Real-World Results with Decision Optimization - Dan Becker
We talked about:
How we make decisions with machine learning

What is decision optimization

Specifying the decision function

Emulation for making the best decisions

Decision optimization and reinforcement learning

Getting started with decision optimization

Trends in the industry

Links:
https://datatalks.club/people/danbecker.html

https://www.decision.ai/

Join DataTalks.Club: https://datatalks.club/slack.html
56 min
February 12, 2021Feature Stores: Cutting through the Hype - Willem Pienaar
We covered:
What is a feature store

Problems it solves

When to use a feature store

When not to use a feature store

The main components

When a team should start using a feature store

Links:
Feast: https://feast.dev/

https://www.tecton.ai/blog/what-is-a-feature-store/

https://docs.greatexpectations.io/en/latest/reference/core_concepts.html

Join DataTalks.Club: https://datatalks.club
1 hr 2 min
February 05, 2021The Rise of MLOps - Theofilos Papapanagiotou
We covered:
What is MLOps

The difference between MLOps and ML Engineering

Getting into MLOps

Kubeflow and its components, ML Platforms

Learning Kubeflow

DataOps
And other things

Links:
Microsoft MLOps maturity model: https://docs.microsoft.com/en-us/azure/architecture/example-scenario/mlops/mlops-maturity-model

Google MLOps maturity levels: https://cloud.google.com/solutions/machine-learning/mlops-continuous-delivery-and-automation-pipelines-in-machine-learning

MLOps roadmap 2020-2025: https://github.com/cdfoundation/sig-mlops/blob/master/roadmap/2020/MLOpsRoadmap2020.md

Kubeflow website: https://www.kubeflow.org/

TFX Paper: https://research.google/pubs/pub46484/

Join DataTalks.Club: https://datatalks.club
1 hr 3 min