DataTalks.Club

DataTalks.Club

By DataTalks.ClubTechnology
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DataTalks.Club episodes

  • Hacking Your Data Career - Marijn Markus

    We talked about:

    • Marijn’s background
    • Standing out in data science
    • Doing the opposite of what people tell you
    • Don’t shoot the messenger (carefully sharing your findings)
    • Advising the seniors
    • Bite off more than you can chew, then chew
    • Marijn’s side projects (finding value in doing things you find interesting)
    • Building a project portfolio
    • Marijn’s NGO project
    • The importance of a team
    • Open source intelligence (OSINT)
    • The importance of soft skills for data experts
    • Marijn’s LinkedIn growth strategy and tips
    • Links:  

      • Twitter: https://twitter.com/MarijnMarkus
      • LinkedIn: https://www.linkedin.com/in/marijnmarkus/
      • Join DataTalks.Club: https://datatalks.club/slack.html


        Our events: https://datatalks.club/events.html

        56 min
      • Visualising Machine Learning - Meor Amer

        We talked about:

        • kDimensions
        • Being self-employed
        • Visual engineering
        • Constrain yourself to get creative
        • Coming up with ideas
        • Visualising difficult concepts
        • The process of creating visuals
        • Creating visuals
        • Learning to create visuals for engineers
        • Consuming with intention to create
        • Learning by breaking code
        • Earning with visuals
        • Adding visuals to blog posts
        • Meor’s book: visual introduction to deep learning


        • Links:  

          • A Visual Introduction to Deep Learning by Meor Amer: https://gumroad.com/a/63231091
          • kDimensions website: https://kdimensions.com/
          • Book to learn about Figma: https://figmabook.com/
          • Jack Butcher's approach: https://www.youtube.com/watch?v=azhqc4K-GAE 

          • Join DataTalks.Club: https://datatalks.club/slack.html


            Our events: https://datatalks.club/events.html

            53 min
          • From Math Teacher to Analytics Engineer - Juan Pablo

            We talked about:

            • Juan Pablo's Backround
            • Data engineering resources
            • Teaching calculus
            • Transitioning to Analytics
            • Data Analytics bootcamp
            • Getting money while studying
            • Going to meetups to get a job
            • Looking for uncrowded doors
            • Using LinkedIn
            • Portfolio
            • Talking to people on meetups
            • Eight tips to get your first analytics job
            • Consider contracts and temporary roles
            • Getting experience with non-profits
            • Create your own internship
            • Networking
            • Website for hosting a portfolio
            • I’m a math teacher. What should I learn first?
            • Analytics engineering
            • Best suggestion: keep showing up
            • Networking on online conferences
            • Communication skills and being organized

            • Links:

              • Website: https://www.thatjuanpablo.com/
              • Twitter: https://twitter.com/thatjuanpablo
              • BROKE teacher to FAANG engineer Twitter thread: https://twitter.com/thatjuanpablo/status/1475806246317875203
              • LinkedIn: https://www.linkedin.com/in/thatjuanpablo/
              • Join DataTalks.Club: https://datatalks.club/slack.html


                Our events: https://datatalks.club/events.html

                51 min
              • From Data Science to Data Engineering - Ellen König

                We talked about:

                • Ellen’s background
                • Why Ellen switched from data science to data engineering
                • The overlap between data science and data engineering
                • Skills to learn and improve for data engineering
                • Ways to pick up and improve skills (advice for making the transition)
                • What makes a data engineering course “good”
                • Languages to know for data engineering
                • The easiest part of transitioning into data engineering
                • The hardest part of transitioning into data engineering
                • Common data engineering team distributions
                • People who are both data scientists and data engineers
                • Pet projects and other ways to pick up development skills
                • Dealing with cloud processing costs (alerts, billing reports, trial periods)
                • Advice for getting into entry level positions
                • Which cloud platform should data engineers learn?

                • Links:

                  • Twitter: https://twitter.com/ellen_koenig
                  • LinkedIn: https://www.linkedin.com/in/ellenkoenig/
                  • Join DataTalks.Club: https://datatalks.club/slack.html


                    Our events: https://datatalks.club/events.html

                    55 min
                  • Becoming a Data Engineering Manager - Rahul Jain

                    We talked about:

                    • Rahul’s background
                    • What do data engineering managers do and why do we need them?
                    • Balancing engineering and management
                    • Rahul’s transition into data engineering management
                    • The importance of updating your skill set
                    • Planning the transition to manager and other challenges
                    • Setting expectations for the team and measuring success
                    • Data reconciliation
                    • GDPR compliance
                    • Data modeling for Big Data
                    • Advice for people transitioning into data engineering management
                    • Staying on top of trends and enabling team members
                    • The qualities of a good data engineering team
                    • The qualities of a good data engineer candidate (interview advice)
                    • The difference between having knowledge and stuffing a CV with buzzwords
                    • Advice for students and fresh graduates
                    • An overview of an end-to-end data engineering process

                    • Links:

                      • Rahul's LinkedIn: https://www.linkedin.com/in/16rahuljain/
                      • Join DataTalks.Club: https://datatalks.club/slack.html


                        Our events: https://datatalks.club/events.html

                        52 min
                      • A/B Testing - Jakob Graff

                        We talked about:

                        • Jakob’s background
                        • The importance of A/B tests
                        • Statistical noise
                        • A/B test example
                        • A/B tests vs expert opinion
                        • Traffic splitting, A/A tests, and designing experiments
                        • Noisy vs stable metrics – test duration and business cycles
                        • Z-tests, T-tests, and time series
                        • A/B test crash course advice
                        • Frequentist approach vs Bayesian approach
                        • A/B/C/D tests
                        • Pizza dough

                        • Links: 

                          • Jakob's LinkedIn: https://www.linkedin.com/in/jakob-graff-a6113a3a/
                          • Product Analyst role at Inkitt: https://jobs.lever.co/inkitt/d2b0427a-f37f-4002-975d-28bd60b56d70

                          • Join DataTalks.Club: https://datatalks.club/slack.html


                            Our events: https://datatalks.club/events.html

                            55 min
                          • Machine Learning System Design Interview - Valerii Babushkin

                            We talked about:

                            • Valerii’s background
                            • Who goes through an ML system design interview
                            • System design VS ML System design
                            • Preparing for ML system design interviews
                            • Machine learning project checklist
                            • The importance of defining a goal and ways of measuring it
                            • What to do after you set a goal
                            • Typical components of an ML system
                            • Applying ML systems to real-world problems
                            • System design and coding in interviews for new graduates
                            • Humans in the validation of model performance

                            • Links:

                              • Valerii's telegram channel (in Russian): t.me/cryptovalerii
                              • Join DataTalks.Club: https://datatalks.club/slack.html

                                Our events: https://datatalks.club/events.html

                                55 min
                              • Career Coaching - Lindsay McQuade

                                We talked about:

                                • Lindsay’s background
                                • Spiced Academy
                                • Career coaching role
                                • Reframing your experience
                                • Helping with career problems
                                • Finding what interests you
                                • Tailoring a CV and “spray and pray”
                                • Career coaching outside a bootcamp
                                • Imposter syndrome
                                • After bootcamp
                                • Internships
                                • Working with recruiters
                                • Networking on LinkedIn

                                • Links:

                                  • Lindsay's LinkedIn: https://www.linkedin.com/in/lindsay-mcquade/
                                  • Impostor questionnaire: http://impostortest.nickol.as/

                                  • Join DataTalks.Club: https://datatalks.club/slack.html

                                    Our events: https://datatalks.club/events.html

                                    53 min
                                  • Product Management Essentials for Data Professionals - Greg Coquillo

                                    We talked about:

                                    • Greg’s background
                                    • Responsibilities of Data Product Manager
                                    • Understanding customer journey
                                    • Interviewing business partners and decision-makers
                                    • Products sense, product mindset, and product roadmap
                                    • Working backwards
                                    • Driving the roadmap
                                    • Building a roadmap in Excel
                                    • Measuring success
                                    • Advice for teams that don’t have a product manager

                                    • Links:

                                      • Greg's LinkedIn: https://www.linkedin.com/in/greg-coquillo/

                                      • Join DataTalks.Club: https://datatalks.club/slack.html

                                        Our events: https://datatalks.club/events.html

                                        54 min
                                      • Recruiting Data Professionals - Alicja Notowska

                                        We talked about:

                                        • Alicja’s background
                                        • The hiring process
                                        • Sourcing and recruiting
                                        • Managing expectations
                                        • Making the job description attractive
                                        • Selecting profiles during sourcing
                                        • Profile keywords
                                        • The importance of a Master’s vs a Bachelor’s degree vs a PhD
                                        • Improving CV
                                        • Interview with the recruiter
                                        • Salary expectations
                                        • Advice for “career changers”
                                        • Cover letters
                                        • Data analysts
                                        • Double Bachelor’s degrees
                                        • The most difficult part of hiring
                                        • Coursera courses on the CV
                                        • Making a good impression on recruiters

                                        • Join DataTalks.Club: https://datatalks.club/slack.html

                                          Our events: https://datatalks.club/events.html

                                          58 min

                                        About DataTalks.Club

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                                        DataTalks.Club - the place to talk about data!

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