Data Scientist - 10 Best Practices, Portals & Career Development

Colleagues, this post will help you accelerate your career and income potential in the Data Science domain. Whether you are new to Data Science or or looking to advance your existing Data Scientist career this post has valuable information for you.

Best Practices

1. Master Core Foundations: Solidify your understanding of statistics, probability, linear algebra, and programming (Python/R), crucial for building robust models (Codecademy, Masters in Data Science).

2. Build a Strong Portfolio: Create diverse, impactful projects on platforms like Kaggle and GitHub, demonstrating end-to-end problem-solving and deployment skills.

3. Specialize Strategically: Focus on niches like NLP, computer vision, or MLOps, aligning with emerging industry demands (Hugging Face, OpenAI).

4. Embrace Cloud Platforms: Learn to deploy and manage data science solutions on major cloud providers (Google Cloud Data Science, Microsoft Azure AI).

5. Develop Data Visualization & Storytelling: Master tools like Power BI or Tableau to effectively communicate insights to non-technical stakeholders (Tableau.com).

6. Stay Current with Research: Regularly follow advancements in AI and ML from leading labs (DeepMind, OpenAI) and research publications (MIT Technology Review, X/Stats_Feed).

7. Practice MLOps: Understand the operational aspects of deploying, monitoring, and maintaining models in production environments.

8. Network and Collaborate: Engage with the data science community online (Kaggle forums, X) and in person to learn and find opportunities.

9. Pursue Lifelong Learning: The field changes constantly; commit to continuous education through courses, certifications, and hands-on experimentation.

10. Cultivate Business Acumen: Understand the business context and how data science solutions drive tangible value and impact organizational goals.

Resource Portals

• Coursera 

• Code Academy 

• Data Science on Google Cloud 

• Kaggle.com 

• Master’s in Data Science 

• Microsoft Power BI

• Tableau

• World of Statistics (X)

Specializations, Master Classes and Certifications

• Applied Data Science Specialization 

• Data Analytics Professional Certificate 

• Data Science: Foundations using R Specialization

• Data Science Fundamentals with Python and SQL Specialization

• Data Science Specialization

• Data Visualization with Tableau Specialization

• Data Science with Python and R

• Google Data Analytics Professional Certificate 

• IBM Data Analyst Professional Certificate

• IBM Data Science Professional Certificate

• Microsoft Power BI Data Analyst Professional Certificate (Exam PL-300) 

• Understanding Data Science 

Enroll today (teams & executives are welcome).  

Download your free Data Science  - Career Transformation Guide.

Explore our Data-Driven Organizations Audible and Kindle book series on Amazon:

1 - Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

Much success in your career journey, Lawrence E. Wilson - Data Science Academy (share with your team)

Data Science - Interviews, Project Portfolios & Certifications (Your competitive edge)

Colleagues, are you seeking to land the next job in your Data Science  journey … either within your current company or with a new employer? All hiring managers need to answer three fundamental questions in the interview process before making a job offer.

Interviews

1. Skills: Can you do the job?

2. Motivation: Will you do the job?

3. Fit: Will you be a team player and fit into the company culture?

Professional Portfolio

Creating a high qualityData Science professional portfolio combined with having industry-leading certifications - along with relevant work experience - will put you at the top of the candidate pool when answering the “Skills” question.:

What is a Project Portfolio? 

1. A project portfolio is a collection of projects, programs, and operations managed collectively to achieve strategic objectives. 

2. It demonstrates your diverse skills, experience, and proven ability to deliver results, showcasing your value and strategic impact to potential employers or for internal advancement.

What Makes a Project Portfolio Valuable?

1. Strategic Alignment: Connecting projects to organizational goals.

2. Resource Management: Efficient allocation of people and assets.

3. Risk Management: Identifying and mitigating potential threats.

4. Performance Monitoring: Tracking progress and outcomes.

5. Stakeholder Communication: Keeping all parties informed and engaged.

What are the best portals to host your project portfolio?

1. GitHub

2. LinkedIn

3. Behance

4. Dribbble

5. Kaggle

6. Hugging Face

7. Personal Website (WordPress, Wix, Squarespace, Webflow - Offers maximum customization & a professional brand presence)

Industry-Leading Certifications & Training

• Applied Data Science Specialization 

• Data Analytics Professional Certificate 

• Data Science: Foundations using R Specialization

• Data Science Fundamentals with Python and SQL Specialization

• Data Science Specialization

• Google Data Analytics Professional Certificate 

• IBM Data Analyst Professional Certificate

• IBM Data Science Professional Certificate

• Microsoft Power BI Data Analyst Professional Certificate (Exam PL-300) 

• Understanding Data Science 

Enroll today (teams & executives are welcome).  

Download your free Data Science  - Career Transformation Guide.

Explore our Data-Driven Organizations Audible and Kindle book series on Amazon:

1 - Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

Much career success, Lawrence E. Wilson - Data Science Academy (share with your team)

Python Data Visualization

Colleagues, the “Python Data Visualization” program will teach you the basic principles of data visualization and how to implement them using various Python data visualization platforms and how to create impactful visuals, animations and dashboards. As data grows in volume and complexity, the importance of effective visualization increases. This video explores how the human visual cortex processes colors and shapes and how we can utilize these mechanisms for effective visualization using Python’s powerful visualization libraries. Starting with pandas and matplotlib--two core Python libraries--you learn the basics of Python data pre-processing and visualization before moving on to more advanced packages. Seaborn, built on top of matplotlib, simplifies common tasks and enhances productivity. Interactive visualizations using bokeh and plotly are also explored. You will use Jupyter Notebooks to craft our visualizations. Learn how to utilize an understanding of the fundamentals of human perception in designing data visualizations, identify the best visualization for a specific dataset, make effective use of matplotlib and seaborn, use seaborn and matplotlib together for best results along with bokeh and plotly to produce interactive plots, and generate animations with matplotlib and plotly. Skill-based training lessons include: 1) Human Perception, 2) Analytical Design, 3) Data Cleaning and Visualization with Pandas, 4) Matplotlib, 5) Matplotlib Animations, 6) Jupyter Widgets, 7) Seaborn, 8) Bokeh, and 9) Plotly. 

Enroll today (teams & executives are welcome): https://imp.i384100.net/y20m12  

Download your free Data Science  - Career Transformation Guide.

Explore our Data-Driven Organizations Audible and Kindle book series on Amazon:

1 - Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age (Audible) (Kindle) 

Much career success, Lawrence E. Wilson - Data Science Academy (share with your team)

Data Science Specialization

Colleagues, the “Data Science Specialization” program is a 10-course introduction to data science, developed and taught by leading professors. Use R to clean, analyze, and visualize data. Navigate the entire data science pipeline from data acquisition to publication. Use GitHub to manage data science projects. Perform regression analysis, least squares and inference using regression models. Acquire high-demand skills in Github, Machine Learning, R Programming and Regression Analysis. This Specialization covers the concepts and tools you'll need throughout the entire data science pipeline, from asking the right kinds of questions to making inferences and publishing results. In the final Capstone Project, you’ll apply the skills learned by building a data product using real-world data. At completion, students will have a portfolio demonstrating their mastery of the material. Skill-based training modules cover: 1) The Data Scientist’s Toolbox, 2) R Programming, 3) Getting and Cleaning Data, 4) Exploratory Data Analysis, 4) Reproducible Research, 5) Statistical Inference, 6) Regression Models, 7) Practical Machine Learning, 8) Developing Data Products and 9) Data Science Capstone.

Enroll today (teams & executives are welcome): https://imp.i384100.net/y20m12  

Download your free Data Science  - Career Transformation Guide.

Explore our Data-Driven Organizations Audible and Kindle book series on Amazon:

1 - Data-Driven Decision-Making  (Audible) (Kindle)

2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)

3 - The Upskill Gambit - Discover the 5 Keys to Your Career and Income Security in the Digital Age (Audible) (Kindle) 

Much career success, Lawrence E. Wilson - Data Science Academy (share with your team)