The Exact Skills and Certifications for an Entry Level Machine Learning Engineer

the data janitor
22 Dec 202203:25

Summary

TLDRThe video script emphasizes the importance of specific skills for securing a job as a machine learning engineer. It suggests that while a bachelor's degree is a baseline requirement, the real value lies in practical experience with SQL, as most machine learning models are sourced from SQL-compatible databases. The ideal candidate should also be proficient in machine learning, Python, and libraries such as scikit-learn, pandas, and XGBoost. Additionally, knowledge of data cleansing and applied statistics is crucial. Cloud skills are also necessary, with a Google Certified data engineering certificate being a notable asset. The video recommends starting with an entry-level role like data analyst to gain SQL experience. It also downplays the need for extensive math and modeling knowledge, as these aspects are largely automated and standardized in the industry. Certifications, while not always indicative of skill, are often used by recruiters to filter resumes, making them an essential part of job hunting.

Takeaways

  • πŸŽ“ **Bachelor's Degree Requirement**: Most companies require a bachelor's degree for a machine learning engineering role, but the specific field of study is often not crucial.
  • πŸ“Š **SQL Proficiency**: SQL skills are highly valued, with 95% of machine learning engineering roles requiring experience, as many models are sourced from SQL-speaking databases.
  • 🚫 **No Entry-Level SQL**: Merely knowing SQL isn't enough; candidates need to have a job where they are actively working with SQL.
  • πŸ‘· **Starting with Data Analyst Role**: For those without SQL experience, starting as a data analyst is a recommended path, as it often involves SQL usage.
  • πŸ€– **Machine Learning Knowledge**: Familiarity with machine learning concepts and Python is essential, along with proficiency in libraries such as scikit-learn, pandas, and XGBoost.
  • 🧼 **Data Cleansing Skills**: Knowledge of data cleansing is important for preparing datasets for machine learning models.
  • πŸ“ˆ **Applied Statistics**: A strong understanding of applied statistics is necessary for a machine learning engineer.
  • ☁️ **Cloud Skills**: As most models are built in the cloud, having cloud-related data skills, such as those covered in the Google Certified Data Engineering certificate, is beneficial.
  • πŸ“ˆ **Experience with Data Tools**: Experience with tools like Power BI or Tableau is advantageous and often listed as a requirement for machine learning engineering roles.
  • πŸ“š **Certifications Matter**: Certifications, such as a Cloud certification and a Google Certified Machine Learning Engineering certificate, can significantly boost a resume and job prospects.
  • πŸ” **Modeling as a Solved Problem**: In applied machine learning, the selection and application of models are often standardized, reducing the need for extensive mathematical and modeling expertise.

Q & A

  • What is the first requirement for a machine learning engineering role?

    -The first requirement is having a bachelor's degree. Companies typically do not specify the field of study or the institution, they just require the candidate to have one.

  • Why does the speaker say that SQL skills are essential for a machine learning engineer?

    -SQL skills are essential because most machine learning models are sourced from relational databases or databases that use SQL. SQL experience is expected as machine learning engineering is not an entry-level role.

  • What is the recommended entry-level role for someone aiming to become a machine learning engineer?

    -The best entry-level role for a machine learning engineer is a data analyst, as many machine learning engineering roles have skills related to data analysis.

  • Which programming language and libraries are important for a machine learning engineer to know?

    -Python is important, along with libraries used in machine learning such as scikit-learn, pandas, and XGBoost.

  • What are the additional skills a machine learning engineer should have?

    -A machine learning engineer should have a solid grasp of data cleansing and applied statistics, as well as cloud skills related to data, such as the Google Certified Data Engineering certificate.

  • What does the speaker suggest about the importance of certifications in the job application process?

    -Certifications are used by recruiters to filter out resumes. Having certifications like the Google Certified Machine Learning Engineering certificate can help secure interviews and eventually a job.

  • What is the speaker's opinion on the role of math and modeling in applied machine learning?

    -The speaker believes that there is very little math involved in applied machine learning and that modeling has been automated and democratized, making it a solved problem in the industry.

  • What is the recommended duration of experience for an ideal entry-level machine learning engineer resume?

    -The ideal entry-level machine learning engineer resume should have three years of experience.

  • What are the two specific certifications mentioned that would be beneficial for a machine learning engineer?

    -The two specific certifications mentioned are the Google Certified Data Engineering certificate and the Google Certified Machine Learning Engineering certificate.

  • Why does the speaker suggest starting with Power BI or Tableau for someone new to the field?

    -Starting with Power BI or Tableau is suggested because these tools are part of the data analyst's skill set, which is considered the best entry-level role for someone aiming to become a machine learning engineer.

  • What does the speaker imply about the current state of model selection in machine learning?

    -The speaker implies that model selection has become standardized, with the best model for a given problem being widely known and used in the industry.

  • How does the speaker view the role of a bachelor's degree in the context of IT and machine learning?

    -While the speaker acknowledges that degrees are often considered useless in IT, they emphasize that having a bachelor's degree is still a requirement set by companies for a machine learning engineering role.

Outlines

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Keywords

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Highlights

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Transcripts

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Related Tags
Machine LearningSQL SkillsPythonData ScienceCloud CertificationCareer AdviceData AnalystApplied StatisticsGoogle CloudEntry-LevelProfessional Development