Aug 1, 2023

Top 7 Data Science Courses [August 2023]

Summary

Enhance your skills with our live, online data science courses. Learn from industry experts in a vibrant, collaborative community setting. Dive into real-world projects, engage in interactive sessions, and build a robust data science portfolio.

Data Science Courses

In the rapidly evolving field of data analytics, the pursuit of proficiency is paramount for aspiring data scientists. Whether you're a seasoned professional or embarking on your journey to learn data science, selecting the right data science course is a critical decision.

With the rise of machine learning and complex algorithms, a well-curated course can significantly enhance your skills and knowledge in data science. Regardless of your background, these data science courses cover a wide variety of topics including data analytics fundamentals, machine learning, data mining, data manipulation and much more.

This article explores some top performing data science courses hosted on Maven, carefully handpicked to guide you through the multitude of options, keeping in line with the highest-quality, meticulously designed educational experiences.

Jump Into Data Science in Python

⭐️9.3 (3 ratings)

Jump Into Data Science in Python is an intensive three-week data science course conducted by Yale faculty and data scientists, Dr. Elena Grewal and Sarah McGowan. It aims to help students transition from spreadsheet tools, such as Excel, to comfortably coding in Python. This 'flipped class' entails students watching self-paced, tailor-made videos and engaging in twice-weekly, hands-on practice sessions.

Ideal for individuals with familiarity in handling datasets and a solid understanding of high school math, the course covers Python basics, data loading and cleaning, data visualization, basic statistics, and problem-solving strategies for roadblocks.

Students learn through Python notebooks, the tool of choice for data scientists. The course is based on a highly-rated class taught by the instructors at the Yale School of Environment.

A former student shares,

Sarah and Elena do a great job of explaining the course content and making sure you understand it. Covered the most important topics in using Python for data science work, and gave great examples and tutorials.

Learn more about Jumping Into Data Science here.

Accelerating Innovation with AB Testing

⭐️ 8.9 (16 ratings)

Accelerating Innovation with AB Testing is a 2-week, data science course hosted by Dr. Ronny Kohavi, a recognized technical expert with experience at Microsoft, Amazon, and Airbnb. The course offers practical insights into designing and analyzing trustworthy A/B tests, integrating AI/ML, and growing businesses through systematic experimentation.

The course provides real-world examples and stories, drawn from over 20 years of professional experience in data science and machine learning, exposing students to the humbling reality that assessing ideas is often fraught with errors. Topics include the importance of the Overall Evaluation Criterion (OEC), common pitfalls, ethical considerations, and the unaddressed challenges in experimentation.

Through a 10-hour curriculum, students will learn about key benefits of A/B tests, how to analyze data cultural challenges within organizations, AI and Machine Learning modeling with a focus on intuition over statistics, and complementary techniques such as quasi-experimentation. The course also allows for customization through requested topics and a Q&A session.

Participants of varying backgrounds, from data scientists to novices, have praised the course for its ease of understanding, depth, real-life examples, and practical insights. Dr. Kohavi's teaching is appreciated for its clarity and expertise, as expressed by testimonials,

Ronny made the content amazingly easy to consume...I can't recommend it enough

- Dylan Lewis, Experimentation Leader at Atlassian.

Learn more about Accelerating Innovation with AB Testing.

Hands-on 3 Data Projects in 5 Weeks

⭐️ 9.8 (4 ratings)

Hands-on 3 Data Projects in 5 Weeks is a data science course that equips learners with in-demand data analysis and programming skills through hands-on projects.

Led by experienced data scientist, Jesús López, the course offers clear explanations and progressively challenging exercises to enhance Python proficiency.

Over the five weeks, students will complete three data projects for their professional portfolios, using datasets of their interest. They will also learn to leverage ChatGPT as a coding assistant, implement efficient coding practices, and make data-driven decisions with any dataset.

The course includes guided in-session practice with Jesús, ensuring personalized support and direction. It covers topics like data visualization, overfitting in machine learning, web scraping, APIs, Streamlit, survival analysis, algorithmic trading, and deep learning.

A testimonial from a previous student reflects the course's efficacy

It exceeded my expectations, and I learned Python with confidence!

The course is ideal for data scientists looking to gain a competitive edge in the job search for programming roles.

Learn more about the course here.

Advance Your Data Science Career with Proven Strategies

⭐️9.7 (7 ratings)

Advance Your Data Science Career with Proven Strategies is a two-week data science course designed to equip data scientists with essential skills for advancing their careers. This course is hosted by Daliana Liu, an ex-Amazon senior data scientist with over seven years of experience in the field.

The course content is rooted in Liu's own career experiences and focuses on essential topics such as persuasive communication, project management, leadership, and career development.

Students will learn how to effectively communicate their projects, build influence within their teams, handle high-impact projects, and navigate the path to promotions. The data science course also offers guidance on how to deal with ambiguity, negotiate deadlines, and understand whether the quality of work meets expectations.

Additionally, it will assist participants in determining their own career paths, distinguishing between manager and individual contributor roles, and identifying their unique edge in the industry. The course includes four live sessions, personalized Q&As, and a three-month office hour service following the course.

A student testimonial states:

Daliana's course gave me the confidence to navigate complex projects and stakeholder interactions effectively. The lessons I learned have directly contributed to my promotion within my team.

Learn more about the course here.

Intro to R for UX Researchers

⭐️9.1 (8 ratings)

Intro to R for UX Researchers is a concise, data science course designed to expand your data analysis toolkit. Hosted by Alex Leavitt, a seasoned social scientist with experience at Meta, PlayStation, Disney, and Microsoft Research, this three-day course for data scientists focuses on statistical analysis, visualization, and storytelling techniques for UX Research using R programming.

The curriculum, which spans 10 hours over three days and an optional orientation day, is accessible to anyone, regardless of their research experience level. As part of the User Research Fundamentals curriculum, the course covers both qualitative and quantitative UX Research methods. Participants learn the basics of R, how to apply R to UX Research, and key skills in data analysis and visualization.

The course has received positive testimonials, with one student, Dina Dajani, lauding the interactive and practical approach which allowed her to write code for real-time projects, greatly enhancing its relevance and long-term benefits.

Another student, Saeideh Bakhshi, highly recommends the course for those seeking to crunch, analyze, and visualize complex data. The course is taught in an inclusive and supportive environment, ensuring students feel comfortable as they learn new skills. It aims to provide students with an essential foundation in data analysis and the ability to create compelling narratives from data.

Learn more about the course here.

Data Storytelling Bootcamp

⭐️10.0 (8 ratings)

Data Storytelling Bootcamp is a two-week data science course that focuses on turning data into compelling narratives that inspire action. Guided by Evelina Judeikytė, an experienced information designer, the course aims to equip participants with the tools to structure, design, and present data analysis and insights effectively.

The course covers crafting a compelling message and narrative arc, understanding the intricacies of visual perception and information hierarchy, developing strategies for engaging presentations, and mastering a design process inspired by UX design and journalism best practices. The course is hands-on, involving interactive workshops and peer feedback sessions.

As a student, Pierre Auguste, Founder and CEO of Vinotracker, shares,

Evelina has a very didactic and efficient data storytelling approach. She coaches with a lot of simplicity, kindness and a real concern for adoption. We co-constructed my first data story and produced a beautiful result: she's very inspiring to work with!

This course is ideal for anyone interested in enhancing their data science skills and learning how to convey data-driven insights in an engaging and impactful way.

Learn more about the course here.

Fundamentals of Data Analysis Using Pandas

⭐️9.3 (3 ratings)

Fundamentals of Data Analysis Using Pandas is a four-day interactive data science course taught by Matt Harrison, a seasoned trainer and author with over 20 years of experience in Python and data science.

This course is designed to help data scientists master patterns in the Pandas library to write clean, optimized code and prepare for machine learning applications. Students will learn to load and prepare data, clean numeric, categorical, and date data, and create effective exploratory data analysis (EDA) and visualizations.

The course also covers how to organize code and notebooks for easy collaboration and sharing. Feedback on individual work is provided, and students are encouraged to learn from the solutions of their peers.

A student, Norman B, a Reliability Engineer, shares,

I liked the format and the structure of the examples made a lot of sense. I think in our engineering community sometimes struggles with the unrealistic example data we must work with that it’s hard to relate back to our jobs.

This course is excellent for those looking to enhance their data science skills using the powerful Pandas library.

The future of data science is thrilling, and it beckons those ready to dive into its multifaceted domains. The data science courses listed here offer a diverse range of topics, from machine learning to advanced data analytics, exploratory data analysis to statical analysis, tailored for both newcomers wishing to learn data science and veterans aiming to sharpen their skills.

Investing in a top-notch data science course not only opens doors to exciting opportunities but fosters the development of the next generation of data scientists. Make an informed choice today, and take the essential step towards a fulfilling and innovative career as a data scientist.