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From Istanbul to New York: Nejla Gul-Saglam’s Inspiring Path to Education and Empowerment

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From Istanbul to New York: Nejla Gul-Saglam’s Inspiring Path to Education and Empowerment

When Turkish native Nejla Gul-Saglam began her journey in Computer Programming at Sakarya University, in Turkey, back in 2007, she didn’t yet know how many times her dreams would evolve—and be tested. Today, as a full-time engineering management professional, mother, and proud 2025 graduate of the Master of Engineering in Engineering Management from CU Boulder, Nejla’s story is one of resilience, support, and adaptability in her relentless pursuit to further her education.

A Passion for Teaching, Shifted

Nejla’s career began in tech, but her heart had always been drawn to teaching. Influenced by her grandparents, she first pursued an associate degree in computer programming and later enrolled in a bachelor’s degree program with the hopes of becoming a teacher. While pursuing her bachelor’s, she began to fulfill her dream by teaching at a nonprofit organization in Istanbul. However, she knew that in order to move forward, she needed to complete her degree.

Amidst the start of her experience as a teacher, and shortly after marrying her husband, Nejla found out she was pregnant, temporarily putting her dreams on hold. Her husband’s work required him to move between the United States and Turkey, a situation that would only become more challenging with a newborn in the picture. So, with just three classes remaining in her bachelor’s degree program, her life began to shift. 

Starting Over, One Course at a Time

“When we arrived in the U.S., I was aware that it was not gonna be easy to gain acceptance, especially as a woman who was coming from a totally different culture,” Nejla recalls. “But I never stopped believing. It has always been my dream to study abroad, experience world-class education, explore new cultures, and build bridges between different cultures.”

Determined to adapt and thrive, Nejla discovered new learning opportunities on Coursera. “I was looking to find a place where I could add meaningful value, despite my English skills being very basic.” With this goal in mind, Nejla refined her English skills on Coursera, all while taking classes in business and computer science, too. “I signed up for a lot of classes—maybe more than 200!” she recounts. 

What started as an effort to improve her English quickly evolved into a deep dive back into the tech world, where her education originally began. She took courses in software development, AI, product development, project management, and communication, including certifications from organizations like IBM, Google.

However, economic limitations and a still incomplete bachelor’s degree made formal education difficult. Nejla says, “I only had three courses left before we had to move to the United States.” Additionally, due to challenges that she faced in waiting for her transcripts to be sent from Turkey, re-enrolling in school became an even bigger hurdle. While she waited, she completed over 40 certificate programs through Coursera Plus and other online platforms — an effort that significantly boosted her career and helped her to land more senior roles in technology.

“I was determined to overcome biases and transform my differences into a strength for leadership. I’ve always genuinely cared about those around me and have been driven by a desire to help make the world a better place. My securing a respectable job in New York City and proving that success is possible even without being a native English speaker or having studied in the U.S. inspired many women in our community to start to believe in their own potential, too.”

A Turning Point: ChatGPT and a New Path Forward

Despite her hard work with online certificates and sleepless nights studying over 20 managerial books she had ordered for independent study, Nejla was feeling hopeless in her pursuit of achieving a degree. With her bachelor’s still incomplete and her transcripts seemingly stalled out, she began to question whether university was still a realistic option. She then asked ChatGPT a pivotal question: “Is there a university that offers a master’s degree without a bachelor’s?” 

That search led her to the University of Colorado Boulder’s Master of Engineering in Engineering Management, and its Performance-Based Admissions (PBA) pathway. This was the moment everything changed. Nejla submitted an inquiry and was contacted by Coursera enrollment representative, Carolyn. 

“I was on the verge of tears,” Nejla says. “Carolyn was incredible—she recognized my deep commitment to education and personal growth. She encouraged me, saying, ‘Nejla, you can do this.’ She believed in me because she could see the journey I had taken through Coursera history and other external education.“

Leveling Up Her Learning

With her manager’s full support, Nejla began the performance-based coursework that would determine her eligibility for the master’s program. She excelled, completing multiple specializations in leadership and project management with top grades.

Even better, with course stackability, Nejla was able to upgrade some of the coursework she’d been doing on Coursera for credit toward her degree once she enrolled. After years of struggle, Nejla was elated to learn this was an option and finally had her hard work pay off.

“It was exactly what I had been looking for — a flexible program that let me move at my own pace. I was already coming from the heart of the tech industry with proven experience, and I had completed prestigious certificate programs. I managed the costs step by step, partnered with my employer for support, and just kept moving forward.” 

Nejla notes that one of her favorite aspects of the program was its self-paced format and flexibility. “It aligned perfectly with my productive morning routines and my hectic schedule as a corporate professional and a mom.”

A Proud Graduate

As a 2025 graduate of the program, Nejla’s learning journey has far from stopped. This year, she has been accepted into a doctoral program in Strategic Leadership at Liberty University.

“This is a huge milestone for me. Now, with a diploma recognized in the U.S., it feels like I’m finally being seen. I’ve come a long way, and I’m proud of the journey I’ve taken. I’ll keep working hard to make those who stood by me witness yet another milestone along the way.”

Gratitude and Inspiration

“I know I couldn’t have done this alone,” she says. “I’ll always be thankful for the people who stood by me through it all. This may be my story, but their support is woven into every part of it. They have each been a valuable part of my journey as guiding lights along the way.”

Nejla’s story is an inspirational one, to say the least, and paints a clear picture that with determination, support, and the flexibility of online learning, any personal goal can be achieved. 

A Note of Thanks, from Nejla

Nejla credits her success to a combination of unwavering inner drive, the opportunities offered by online learning, and the incredible support of key people in her life. Her husband Kemal stood by her as a true partner, taking on homemaking so she could focus on her goals. Zeynep, her daughter, showed remarkable patience, standing by her every step of the way as she proved herself. She would always offer encouragement that made all the difference. Her mentor, Mike, was the first person to truly believe in her potential when she arrived in the U.S. He offered unwavering support, providing valuable suggestions on how to create a healthy work-life balance while developing a leadership journey. Her manager Eric was very supportive with diligently following up on all the back-and-forth emails to ensure her tuition support was approved and processed. Beyond that, he created a supportive space that allowed her to balance class responsibilities without burning out at work. And Carolyn, from the Coursera enrollment team, not only introduced her to the program but also answered every one of her many questions with kindness and care.

Q&A with Joshua David Tarfa, Gies iMSM Graduate

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Q&A with Joshua David Tarfa, Gies iMSM Graduate

Meet Joshua David Tarfa, a Nigeria-based senior product manager and recent graduate of the University of Illinois’ Gies College of Business Master of Science in Management (iMSM). In just one year, he completed his degree, secured two promotions at work, and managed his own freelance design business.  We sat down with Joshua to hear about his experience, what motivated him to pursue the degree, and how it’s already paying off.

Tell us a bit about your background.

I started out as an illustrator, animator, and graphic designer—completely on the creative side of things. I went to Nile University of Nigeria, where I studied business administration, but after graduation, I couldn’t get into the General Electric program I was aiming for. So I turned to freelance design, and surprisingly, that took off. I had clients from the U.S. and Europe, and it just made more sense financially to work for myself.

Eventually, I transitioned into product management after having been an Illustrator at the uLesson Group. I started the iMSM program soon after. While I was in school, I actually went from associate product manager to product manager and then senior product manager.

Why did you choose an online degree, and why Gies?

The flexibility was a huge factor. Given the tuition and economic crisis, it just made sense. I looked at other online programs, but many were new or didn’t have the level of accreditation I wanted.

Gies had flexibility, reputation, and it was on Coursera. And to be honest, I’m kind of the Coursera guy at my office. I have over 50 certificates—Google Project Management, UX Design, Software Project Management—that’s actually how I broke into product. Plus, Marc Andreessen went to Illinois, and I thought, “Well, that’s a good sign.”

Did you benefit from the degree? What gave you the most value?

Absolutely. From the very beginning, I could apply what I was learning. I remember taking a strategic management course and using concepts from it immediately at work. I mentioned “adverse selection” in a meeting and my boss looked at me, impressed, and was like, “Ahh this guy!” (laughs)

The coursework didn’t just give me confidence—it gave me capability. I could contribute at a higher level right away.

What did you like most about the program?

I loved the case studies because I could pick the companies and the industries. So, I picked my company’s market and the African market in general. There was one that we did on market Intelligence and Porter’s 5 Forces analysis. So I did that based on the market we operate in at Miva, a subsidiary of The uLesson Group. So my assignments would basically turn into content that I could use at work. The way the assignments are structured, they can be directly translated into the real working world.

Have you seen any big changes since graduating?

I feel [getting promoted] was a result of having that extra knowledge from the course. I was an associate for a while, so I felt like beginning to understand strategy and global markets…it enhanced the conversations I was having with stakeholders and how I was thinking about product as a whole.

What motivated you to keep going, especially through such a demanding year?

I’m shy, but I want to be the best in the world. Growing up in Nigeria, I always worried about how I would stack up internationally. Would being a product manager here compare to being one in the U.S.? The program helped with that. I feel much more confident in my skills now. The imposter syndrome has faded.

What advice would you give to someone considering the iMSM?

I always say to friends, “If not now, then when?” It’s an investment, and Gies has been around for over 100 years and Coursera has been around for a while, too. These are trusted institutions, and you won’t come out of the program unchanged. You’ll be more capable, more confident. You just have to commit.

How was your experience with online learning?

It was flexible. There were live lessons, but if I couldn’t attend, I could watch them later. That made things manageable.

For Nigerian learners, the cost is a key consideration. Seeing tuition fees listed in thousands of dollars can be overwhelming, after all, that’s about 20 million naira without a scholarship! But it’s important to note that the fees aren’t paid all at once. It’s a pay-as-you-go model, which makes it much more manageable and accessible.

Did you face any struggles during the program?

Getting promoted twice also meant way more work. Toward the end, I was like… “Oh noo.” (laughs) Some live sessions were at 2 AM Nigerian time, and I couldn’t always attend, also because my workload had increased. It was tough, especially as my role expanded, but I got through it.

Anything else you’d like to share?

Just that it’s definitely doable. I was still managing my own business on the side—not full scale, but still. And I finished in a year. As you can see, I’m still alive! (laughs) But seriously, even if you do it in two years, it’s completely achievable and worthwhile.

What Does a Data Scientist Do?

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What Does a Data Scientist Do?

If you’re not sure what a Data Scientist does, you’re not alone.

At a high-level, a data scientist collects and analyzes large amounts of data to find useful patterns and insights. They use tools like statistics, coding, and data visualization to help businesses make smarter decisions.

In this article, Catherine Zhou, a Data Scientist at Codecademy, provides some insight into the world of data science, talks about her day to day, and helps us answer the elusive question, “What does a Data Scientist do?”

Learn something new for free

But first… what is data science?

The first step to understanding what a Data Scientist does is to understand what data science is. The following definition comes straight out of Code Foundations, a Codecademy career path designed to provide an overview of the main applications of programming.

Data gives us information about the way the world works. And information can carry meaning – from a click telling us what someone likes, to toxins in the water signaling a health concern. But, data is meaningless unless we do something with it. That’s where data science comes in.

Data science enables us to take data and transform it into meaningful information that can help us make decisions. It is interdisciplinary and combines other well-known fields such as probability, statistics, analytics, and computer science.

The work that you might do could range from writing up reports to building machine learning models. No matter what your interests are, data science is applicable – because these days, we have data on everything!

What does a Data Scientist do?

Now that we know what Data Science is, let’s talk more explicitly about what a Data Scientist actually does.

In our interview with Catherine, she says: “there’s a wide range of ways that Data Scientists may work with strategy, decision making, and implementation of analysis. As you can imagine, the role of a Data Scientist may look very different depending upon what company you’re working for, and what business domain you’re working in!”

Below are just a few of the different tasks that a Data Scientist might do:

Data collection and preparation

Data collection and preparation are key parts of a data scientist’s job. The first step to solve any data-related question is to gather the right data. But raw data often comes with errors, missing pieces, or inconsistent formats. So, the next step for a Data Scientist is to prepare the data, which requires cleaning and organizing it. This might involve removing duplicates, fixing typos, converting dates into a standard format, or combining data from different sources. This is a time consuming, but essential process that every Data Scientist must do.

Machine learning

Instead of just analyzing past trends, Data Scientists use machine learning to build models that can learn from patterns and improve over time. For example, they might create a model that predicts customer behavior, detects fraud, or recommends products. To do this, they train algorithms using clean, prepared data and then test and fine-tune the models to make sure they’re accurate.

Data modeling

Data modeling is an important part of a Data Scientist’s job because it helps them understand relationships within the data and structure it in a useful way. By creating models — like diagrams or mathematical frameworks — Data Scientists can organize complex information, define how different pieces of data relate to each other, and set the stage for deeper analysis.

Data visualization

Data visualizations are how Data Scientists can turn complex numbers and patterns into clear, easy-to-understand visuals. Charts, graphs, and dashboards help tell the story behind the data, making it easier for people — especially non-technical audiences — to see trends, compare values, and make informed decisions.

Algorithm development

Algorithms are the rules or instructions that help computers process data efficiently, whether it’s sorting information, finding patterns, or making decisions. Data Scientists often spend time designing and tweaking algorithms to improve accuracy, speed, or relevance for specific tasks.

Mathematical statistics

By using concepts like probability, distributions, and hypothesis testing, Data Scientists can measure uncertainty, test ideas, and draw meaningful conclusions from data. As an example, a Data Scientist might use statistics to determine if a change in a website led to more user sign-ups or if a pattern they see in the data is just random.

Programming

With programming languages like Python, R, and SQL, Data Scientists can automate repetitive tasks, build machine learning models, and create custom tools for specific problems. For example, they might write code to clean messy data, run simulations, or generate reports that highlight key insights.

What’s the difference between a Data Scientist and Data Analyst?

It’s true, both Data Scientists and Data Analysts are focused on turning raw data into actionable insights that can inform better business decisions. However, these roles differ in scope, complexity, and focus.

Data Analysts are typically focused on looking at historical data to answer “what happened?” and “why did it happen?” Their work is often more structured and driven by specific business queries or performance metrics.

Data Scientists, on the other hand, tend to operate at a more advanced level to answer future-facing questions like “what will happen next?”

What is an average Data Scientist salary?

Looking at Indeed, Data Scientists make an average salary of $126,833 per year in the U.S.

Even with less than a year of experience, Data Scientists earn $101,338 on average. Those with three to five years of experience make $138,080 each year, with a high of $201,230.

How do I become a Data Scientist?

There are many different paths to become a Data Scientist, but here’s a look at the different skillsets and college degrees that will help build a strong foundation for a future career.

College Degrees

The best college degrees for aspiring Data Scientists include:

  1. Computer Science: Gives you a solid understanding of algorithms, programming, and data structures, all of which are essential for data manipulation, analysis, and building machine learning models.
  2. Statistics: Helps you master the mathematical and statistical concepts used to analyze data, test hypotheses, and make predictions, which are central to data science.
  3. Data Science: Many universities now offer degrees specifically in data science, which combine elements of computer science, statistics, and machine learning. This degree is tailored to prepare students directly for data science careers.
  4. Mathematics: A degree in mathematics, especially with a focus on applied mathematics or computational mathematics, will equip you with the problem-solving and analytical skills needed to work with complex data sets.
  5. Engineering: Particularly degrees in electrical, software, or systems engineering often have a strong emphasis on programming, data processing, and computational methods, all of which are highly relevant to data science.

Skills

There are a number of skills that are shared by Data Scientists across the board. If you’re thinking of becoming a Data Scientist you’ll want to build your skillset in the following areas:

  • Descriptive and inferential statistics
  • Probability
  • Programming (Specifically SQL, and Python or R)
  • A passion for diving deep into the data for the specific field you plan to work in

Of course, there’s a whole lot to learn in each of these areas. But Catherine explains that you shouldn’t feel like you have to learn it all:

“I’m always humbled by how much more I have to learn. Originally when I broke into the field I felt really overwhelmed and felt a lot of imposter syndrome about having to learn a lot. But I realized that when you work in data analysis or statistics you end up specializing in one part of it.

“You might specialize in predictive analysis; you might specialize in reporting; you might specialize in machine learning or artificial intelligence. There are so many subsets — usually Data Scientists will focus on one thing and get really good at it.

Check out our data science courses to start building the skills you’ll need to launch your career.

Is data science right for you?

When asked if she always wanted to be a Data Scientist, Catherine shared, “This might be weird, but I was also really into probabilistic thinking and used to think about how it applied to my day-to-day decisions. I would try to calculate things like: if I miss this traffic light, what are the chances I’ll miss the next two lights? How much longer would that lengthen my commute?”

If you’ve found yourself trying to make similar calculations, are curious about analyzing human behavior, or get excited about using data to uncover interesting or surprising information, a career in data science may be in your future!

Our Data Scientist: Machine Learning Specialist career path is designed to give you all the skills you need to become a data analyst, data scientist, or machine learning engineer.

Learn more and get started here.

This blog was originally published in April 2021 and has been updated to include updated salaries, and new resources.


Whether you’re looking to break into a new career, build your technical skills, or just code for fun, we’re here to help every step of the way. Check out our blog post about how to choose the best Codecademy plan for you to learn about our structured courses, professional certifications, interview prep resources, career services, and more.

Free Homeschooling Resources: Explore Alison’s Comprehensive Programme

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Free Homeschooling Resources: Explore Alison’s Comprehensive Programme

Since COVID in 2020, homeschooling has become a popular choice for many families who would prefer an alternative to traditional education. Whether you need something that is flexible or a more personalised curriculum, homeschooling provides many advantages. Alison has many great online courses to help you on your homeschooling journey. The platform offers a tailored solution for families with high school-aged children. It also provides the necessary resources to succeed on this journey.

Delve into Alison’s Homeschooling Curriculum

Alison’s Homeschooling Curriculum offers many different courses that have been specifically designed to meet the needs of students at different levels. There are hundreds of topics to choose from and they can be customised easily to meet the needs of young people. Parents can have a hands-on role if they want, while also staying up to date with what their child is learning.
To view the available courses on offer, visit the Homeschooling Hub. Alison offers core curriculum subjects such as mathematics and science, English and languages, as well as electives such as the arts, physical education, coding and humanities. Our suite of AP and CLEP courses help students prepare for college exams while our Career and Technical Education programme helps ready them for the world of work. There really is something for every learner.

Tailor Your Homeschooling Curriculum with Alison

One of the major benefits of Alison’s homeschooling platform, apart from flexibility, is the electives. These are great additions to the core curriculum. They are ideal for students who would like to explore new areas of interest and upskill or simply find out more about a subject they may be passionate about.

Courses available include:

  • Principles of Creative Writing: This course will help students develop their writing skills and knowledge of grammar, while exploring creative expression through storytelling.
  • Global Digital Literacy: This course helps students with the essential skills needed to thrive in the digital world, from online safety to creating engaging content.
  • Introduction to Python: Designed for beginners, it teaches the fundamentals of Python programming, including syntax, variables, loops, conditionals, functions, lists, and dictionaries.

The diversity of electives available means that students can customise their education to match their unique interests, helping them develop a well-rounded set of skills that will serve them for years to come. Whether they have an interest in technology, art, or languages, there’s a course waiting to inspire them.

Why Choose Alison for Your Homeschooling Programme?

  • Flexible Learning: Alison’s courses are designed to be flexible, allowing homeschoolers to study at their own pace, on their own schedule. This flexibility is crucial for homeschool families who may have differing needs or unconventional schedules.
  • Wide Range of Subjects: From core subjects to interesting electives, Alison’s course offerings are vast. No matter what your child is interested in, you can find a course that will engage them while enhancing their learning.
  • Quality Content: Alison is a trusted and credible online learning platform known for its high-quality educational content. The courses are designed and taught by experts in each field. Parents can rest assured that their children will receive quality education that can supplement or even replace traditional learning.
  • Free Access: Alison provides free access to its courses, which is a massive benefit for homeschooling families who may be working with budgets.

An unmatched learning experience

With homeschooling, parents can personalise their child’s learning experience to suit their family and the young person’s specific needs. Alison plays a pivotal role in ensuring that parents are provided with the tools they need to thrive in this structure of learning. Whether you have the time to do it full time or have to work around a schedule, Alison will help you support your child’s academic growth. Taking on this new way of learning will enable your child and you to learn in a way that is tailored for your family,
Visit Alison’s Homeschooling Programme Portal to view all the available courses. With Alison, the possibilities are endless for creating a dynamic and personalised homeschool curriculum.
Homeschooling is not just about following a mundane curriculum; it’s about developing a love of learning from a young age. Alison makes this possible, one course at a time.

Frequently Asked Questions

Q. What makes Alison a good choice for homeschooling families?
Alison offers a flexible, cost-effective, and high-quality learning platform ideal for homeschooling. With thousands of free online courses in both core subjects and electives, families can tailor their child’s education to suit personal interests, academic goals, and individual learning styles. The platform is especially useful for secondary school learners and offers resources that support both academic and career readiness.

Q. Can I customise my child’s homeschooling curriculum on Alison?
Yes, absolutely. One of Alison’s biggest strengths is the ability to personalise the learning experience. Parents and students can choose from a wide range of courses, from traditional subjects like mathematics and English to electives such as coding, music, and digital literacy. This flexibility allows you to create a unique curriculum that matches your child’s strengths and interests.

Q. Are Alison’s courses suitable for college or career preparation?
They are. Alison provides AP and CLEP courses that help students prepare for college-level exams. Additionally, the Career and Technical Education (CTE) courses focus on practical skills and job-readiness, making them ideal for students who want to explore vocational pathways. Whether your child plans to attend university or enter the workforce, Alison has relevant, supportive content to guide them.

Delivering job-relevant learning: New partners, certificates, GenAI content, and a degree pathway

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Delivering job-relevant learning: New partners, certificates, GenAI content, and a degree pathway

By Marni Baker Stein, Chief Content Officer, Coursera

We constantly collaborate with our world-class university and industry partners to expand our catalog. Today, I’m excited to announce several new partners, five entry-level Professional Certificates, an expansion of our GenAI catalog, and a new degree pathway to support learners and institutions worldwide.

New Partners & Specializations

  • American Council on Exercise (ACE)
    Intro to Personal Training – Learn fitness fundamentals, goal setting, behavior change, sales, and client retention in this three-course Specialization.
    • “This Specialization is an accessible pathway for anyone considering a career in fitness, whether they are seeking to explore the basics or build the confidence needed to take the next steps toward professional certification,” said Cedric X. Bryant, PhD, FACSM, ACE President and CEO. 
  • Immersify Education
    Interactive 3D Anatomy & Physiology – Explore body systems with 3D models, gamified quizzes, and real-world scenarios in this beginner-level Specialization.
    • “This partnership between Immersify and Coursera marks a transformative step in the future of education and healthcare training. By combining our cutting-edge immersive learning technology with Coursera’s vast global reach, we are equipping learners with skills they need to thrive in an evolving job market and prepare for careers in the healthcare industry. We have a shared mission to empower learners with the most engaging and effective learning experiences possible to millions of people,” said Chloe Barrett, CEO and Founder of Immersify.
  • Saïd Business School, University of Oxford
    The Intersection of Finance, Strategy, and Sustainability – Discover how to create and measure business value with ESG through sustainable finance and global frameworks.
    • “This programme marks an important step in our partnership with Coursera enabling us to reach new learners globally, and we see this as a major opportunity in bringing Oxford faculty’s expertise to a broader audience to enhance learning experiences worldwide.  This programme affords learners the opportunity to explore the business case for ESG and master the frameworks, standards and best practices for ESG reporting and disclosure. Plus, better understand sustainable finance and learn about the range of sustainable financial products and services available to drive positive change,” said Caroline Williams, Executive Director of Oxford Saïd Online.

New Entry-Level Professional Certificates

Prepare for in-demand, entry-level roles — no degree or prior experience required.

  • DeepLearning.AI – Data Analytics
    Craft persuasive data narratives using Python, Tableau, and GenAI tools in DeepLearning.AI’s first entry-level certificate.
    • “We’ve built a program that combines foundational analytics with state-of-the-art AI technology, teaching learners to extract insights from complex datasets and communicate them effectively – skills in high demand across every industry,” said Sean Barnes, instructor and Data Science & Engineering Leader at Netflix.
  • Microsoft – Python Development
    Learn Python, build web apps with Flask, automate tasks, and deploy on Azure — while managing projects with Agile.
  • Adobe – Marketing Specialist
    Use audience research, content strategy, SEO, and Adobe’s leading design tools to create and analyze campaigns.
  • Johns Hopkins Medicine – Medical Office Manager
    Manage clinics, design EHR plans, implement hiring systems, and optimize revenue in Johns Hopkins’ first entry-level certificate.
  • IBM – Java Developer
    Build a portfolio of Java applications leveraging the latest tech and frameworks like Spring, SQL, and Hibernate.

GenAI Learning at Scale

GenAI course enrollments have grown to 12 per minute in 2025, double what we saw last year.  Our catalog now includes 680+ GenAI courses, including these top new additions:

New Degree Pathway: Google + Illinois Tech

Completing and passing the Google IT Support Professional Certificate grants direct access to enroll in the Master of Information Technology at Illinois Tech.  This allows students to:

  • Save up to $1,500 in tuition. 
  • Start with up to 10% of the degree completed. 
  • Graduate up to 4 months earlier.

Alternatively, students who entered the degree through the Performance-Based Admissions pathway can now earn credit for one of the following Professional Certificates*:

 We’re excited to help more learners unlock new opportunities and take the next step in their careers with these latest offerings.

*Students cannot transfer both the Google IT Support certificate and one of the Professional Certificates. The program will accept one of these. 

Improving Multiple-Choice Retrieval Practice

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Improving Multiple-Choice Retrieval Practice

Results

In Experiment 1, participants who justified their answers scored about 10% higher on the test than those who did not. Importantly, that’s their MC correctness; the researchers didn’t examine their actual justifications (which happens to be great news for busy teachers). When looking at how students thought they would do, there was an interesting interaction. Participants who knew they were going to have to justify their answers were a bit underconfident in how they would perform compared to those who just took the MC test, who were overconfident. But then, after taking the test, both groups were pretty similar in metacognition.

This metacognitive effect is important. One of the benefits of retrieval practice is improved metacognition. By reducing overconfidence, students are more likely to persist in self-directed studying. Simply telling them they will need to explain their answers provided this same benefit that both groups received after practicing retrieval.

In a second experiment, the researchers wanted to see if this effect persisted over a delay, so participants were asked to take the MC test again two days later. While the answer justification group still scored 6% higher, the effect wasn’t significant. This could be due to their smaller sample size, but does give this blogger a little bit of pause. Often, we see that a strategy has an immediate effect that disappears or reverses over time. Given the mechanisms here, I highly doubt that is the case for this study, but further research is certainly needed.

Bottom Line

CU Boulder announces AI master’s degree on Coursera for under $16,000 — no application required

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CU Boulder announces AI master’s degree on Coursera for under $16,000 — no application required

By Marni Baker Stein, Chief Content Officer, Coursera

I’m excited to announce a Master of Science in Artificial Intelligence (MS-AI) from the University of Colorado Boulder (CU Boulder), marking the university’s fifth degree on Coursera.

As demand for AI talent grows, this degree enables anyone to build their AI expertise while earning a credential that stands out in a competitive job market. Nearly one in four U.S. tech jobs require AI skills, and those roles pay up to 25% more.

“In a world increasingly run by intelligent systems, expertise in AI will be the difference between keeping up and leading the way. A master’s in artificial intelligence will empower students to design ethical, responsible machine learning solutions that scale across platforms — from healthcare and finance to social media and robotics. It’s more than technical skill; it’s a commitment to shaping AI that amplifies human potential,” said Kevin Gifford, CU Boulder’s Faculty Director for the MS-AI/MS-CS programs on Coursera.  

Built for working adults, the MS-AI maximizes accessibility, flexibility, and job-relevant learning:

Accessible

  • This program is designed for anyone with a strong background in computer science — no bachelor’s degree, prerequisites, or application required. Learners gain admission by enrolling and earning a B or better in a three-course pathway in machine learning or statistical learning.
  • The degree is $15,750, with all of CU Boulder’s degrees on Coursera priced at about $20,000 or less.

Flexible

Job-relevant learning

  • The interdisciplinary curriculum combines computer science, data science, engineering, and ethics — blending technical depth with social responsibility.
  • Through theory and real-world application, students explore core AI concepts, including neural networks, deep learning, and reinforcement learning, while building the mathematical foundation needed to design and optimize scalable machine learning models.
  • Graduates will qualify for roles like Chief AI Officer, AI Manager, or AI Engineer and can build specialized skills with electives in natural language processing, computer vision, and robotics.

We’re honored to partner with CU Boulder, the pioneers of performance-based admission degrees on Coursera, to remove barriers and expand access for those eager to shape the future of technology.

Enrollment for the MS-AI opens August 20, with classes beginning August 25. Learn more or get started at https://www.coursera.org/degrees/ms-artificial-intelligence-boulder.

*To earn credit, learners must complete additional graded assignments, which are available after paying tuition.

Readers MailBlog err Post

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Readers MailBlog err Post

6 Popular Use Cases for Building AI Skills – What the C-Suite Wants You to Know 

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6 Popular Use Cases for Building AI Skills – What the C-Suite Wants You to Know 

AI is no longer a niche skill — it’s a strategic priority. This is especially true for key use cases and industries. In fact, 45% of C-Suite leaders say AI and machine learning skills are their top areas to upskill in 2025, according to Skillsoft’s C-Suite Perspectives Report.

Companies know it’s no longer just about understanding what AI can do — it’s about actively using AI to meet business goals while fostering innovation and efficiency. 

But, while leaders recognize AI’s potential, many are still struggling to close the gap between ambition and capability. 

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So, how can individuals and teams build the skills required to actually move the needle? We analyzed the most in-demand AI use cases to show where AI is already delivering impact — and how you can upskill to lead the way. 

Insider Tip: For teams looking to build AI and other in-demand tech skills, Codecademy Teams makes it easy to upskill together.  

So, without further ado, let’s take a look at the six most popular AI use cases transforming industries today. 

1. AI for Customer Service  

One of the most rapidly evolving AI use cases is within customer service. When you’re chatting with a support rep, or rebooking a flight, AI is working behind the scenes.  

Using natural language processing (NLP) and machine learning, virtual assistants like ChatGPT are revolutionizing how companies handle inquiries, resolve issues, and process transactions. For professionals in customer experience, understanding how to integrate and train these tools is becoming a critical skill set.  

AI skills you can learn 

  • Intro to ChatGPT. Harness the capabilities of ChatGPT, one of the most talked-about AI tools. Whether automating emails or generating content, this free course teaches how you can enhance customer service and streamline workflows with AI-powered conversation models.  
  • Apply Natural Language Processing with Python. NLP is the reason why ChatGPT can understand our written requests, or autocorrect can predict what we might type next. In this skill path, learn all about how computers work with human language and complete a portfolio-ready project. 
  • Customer Service: Engaging with Customers. While not specifically about AI, this course covers techniques to improve customer engagement, boost self-confidence, and excel in problem-solving. All essential skills when working in customer support. 

2. AI for Healthcare  

Imagine a world where diagnoses are quicker, treatments are more personalized, and patient outcomes dramatically improve. That’s exactly what AI is enabling in the healthcare industry.  

With AI’s ability to analyze massive datasets, healthcare professionals can make more informed decisions, ultimately improving patient outcomes. By developing skills in AI for healthcare, you’ll be contributing to innovations that could save lives, reduce costs, and revolutionize patient care. 

AI skills you can learn 

  • Intro to Generative AI. This course is the perfect launchpad into the world of AI. Explore different types of AI models and discover how this technology is being leveraged to automate and innovate across industries. 
  • Build a Machine Learning Model. Another starting point for AI in healthcare is this machine learning course designed for beginners. Machine learning models can be trained to analyze medical imaging (like CT scans) to identify anomalies, or assist in diagnosis.  
  • Machine Learning/AI Engineer Career Path. This comprehensive path covers building end-to-end machine learning applications. These can then be applied to various healthcare solutions, from predictive analytics to personalized medicine. 

3. AI for Finance  

AI isn’t just influencing investment strategies — it’s transforming the backbone of financial services. On an individual level, financial analysts are using AI to evaluate their clients’ financial history and behaviors. This makes it easier to provide personalized plans, recommendations, and investment strategies.  

At a macro level, many financial institutions are using AI systems to analyze countless transactions and flag fraudulent activity.  

Whether you’re interested in developing fraud detection systems or optimizing trading algorithms, AI in finance offers endless opportunities for career growth. Particularly as digital payments and autonomous banking continue to rise.  

AI skills you can learn 

  • Principles of Data Literacy. Master the fundamentals of data literacy—learn how to interpret, visualize, and analyze data effectively. This recently updated course features interactive components and uses AI for data, giving you hands-on learning by building real-world data skills.  
  • Analyze Financial Data with Python. The best analysts at banks and hedge funds rely on more than Excel to efficiently process data and produce recommendations. In this Skill Path, you will learn to process, analyze, and visualize financial data with Python. 
  • Recognizing Hallucinations, Inaccuracies, and Bias in AI. Understanding the challenges of AI-generated content, such as inaccuracies and biases, is crucial in finance. This helps ensure ethical and accurate AI applications, especially when considering areas like lending, credit scoring, and insurance. 

4. AI for Marketing  

AI in marketing is rapidly becoming one of the most compelling use cases for those looking to build AI skills. In fact, over 80% of marketers are already using AI in some capacity, according to HubSpot.  

From targeted advertising and recommendation systems to customer sentiment analysis and content creation, AI is reshaping the marketing landscape by enabling more efficient and effective strategies. 

The growing demand for AI in marketing means there are abundant opportunities to understand customers on a deeper level and tailor messages like never before. Here are a few tips we put together on how to use ChatGPT to form a marketing plan. 

AI skills you can learn 

  • Intro to MidJourney. You can also use AI to create media assets like pictures and videos to accompany your marketing materials. This course introduces you to MidJourney, which is one of the most popular AI tools for image generation, helping you tap into your creative side.   
  • Prompt Engineering for Marketing. Learn how to use ChatGPT for marketing by using prompt engineering to generate marketing copy and content that engages your audience.  
  • Learn How to Use AI for Marketing. This beginner-level course breaks down how to use generative AI for marketing. You’ll learn how to use tools like ChatGPT and Midjourney for research, strategy, and content creation.

5. AI for Coding  

As software development continues to become increasingly complex, coding has emerged as another popular AI use case. AI tools are helping developers automate repetitive tasks, optimize code, and even assist in debugging.  

A recent survey of the Stack Overflow community found that ChatGPT is the primary code assistant tool that professional developers and people learning to code use. The survey also shows that using AI is transforming how developers approach programming, allowing them to focus on higher-level problem-solving while AI handles time-consuming or error-prone tasks. 

By leveraging AI in coding, you’ll gain hands-on experience with tools that can write code, suggest improvements, and help streamline the development process.  

AI skills you can learn 

  • Learn How to Use AI for Coding. From debugging to optimizing, explore how AI can assist in writing and optimizing code, ultimately reducing development time and improving software quality with AI-powered coding tools.  

6. AI for Data 

Gone are the days when data analysis was a manual, time-consuming task reserved for data scientists alone. Today, AI models can sift through massive datasets in real time, identify patterns, flag anomalies, and even make predictions with impressive accuracy. Whether it’s customer behavior analytics, financial forecasting, or medical research, AI doesn’t just process data — it makes it actionable. Which is why AI for data is a popular use case for business leaders to focus their upskilling efforts.

AI can act as a supportive data analysis co-pilot — automating data cleaning and preparation, suggesting visualizations, and even guiding queries in natural language. Learning these AI for data skills lowers the barrier to entry and helps people become smarter, faster, and more effective with data. 

AI skills you can learn 

  • Learn How to Use AI for Data Analysis. This course will teach you how to use AI tools like ChatGPT or Gemini for data analysis in Python. You’ll learn how to use AI as your personal analytics co-pilot. 
  • Learn How to Use AI for SQL. This beginner-level course focuses on generating SQL with AI, transforming natural language to SQL, and utilizing LLMs for SQL operations.  

How Codecademy can help you build AI skills  

Per Skillsoft’s recently published C-Suite Perspectives Report, while senior executives feel their organizations have moved past the beginning phases of AI, many of their greatest challenges to implement AI skills hasn’t changed. They’re still looking to capitalize on these top AI use cases.

Whether you’re a team leader or an individual contributor, learning about AI with Codecademy is one of the smartest things you can do to further your career in tech.  

Our interactive courses utilize industry-leading AI tools, so you can get hands-on experience working with AI systems as you learn about the concepts that power them.  

And with our career paths, you can build a portfolio of impressive projects that show employers you can apply AI skills to real-world scenarios in these popular AI use cases.  

Want to see what other challenges senior leaders are struggling with? Download Skillsoft’s recently published C-Suite Perspectives Report.  

Retrieval Practice Improves Learning, But Will it Help ALL of My Students? More Experimental Evidence

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Retrieval Practice Improves Learning, But Will it Help ALL of My Students? More Experimental Evidence

Cover image by Prawny from Pixabay

By Megan Sumeracki

In the first year that our blog was created—2016—I wrote a piece titled, Retrieval Practice Improves Learning, But Will it Help ALL of My Students? In this piece, I covered an experiment conducted by Pooja Agarwal and colleagues (1) about the benefits of retrieval practice for students with different working memory capacities. The main question was whether retrieval practice would benefit students with a wide range of working memory capacity—or the ability to hold information in mind and engage in attentional control. It is reasonable to ask whether retrieval practice, given the needed balance of success and difficulty, might benefit students with higher working memory ability more—a rich get richer situation. If retrieval practice only benefits certain types of students, then it would be important to know that! Thankfully, that was not what they found.

The main findings were that retrieval practice led to greater performance on a learning assessment than repeated “studying” or reading, and this was true whether the students had lower or higher working memory capacities (1). In fact, when the learning assessment was completed one week after learning, they students with lower working memory capacity actually benefited more from retrieval practice than those with higher working memory capacity. The authors argued that retrieval practice was beneficial for students with a range of working memory ability, not just students with higher working memory capacity.

In today’s post, I cover another research article asking whether retrieval practice is equally beneficial for students with different skills. Bruna Fernanda Tolentino Moreira and colleagues (2) conducted two experiments, one each with 4th and 6th grade children, investigating whether retrieval practice was equally beneficial for students with different visual word decoding skills. The authors note that children’s visual word decoding abilities tend to differ dramatically, even when looking at children in the same age range. If retrieval practice is less effective, not effective, or harmful for learning for some children, it is important to know this!

Experiments 1 and 2 were very similar. Experiment 1 was conducted with 6th graders, and experiment 2 was conducted with 4th graders. There were a couple of other differences: In Experiment 2 a few additional measures were included. The children also practiced retrieval and restudied twice rather than just once in, and only completed one final assessment test instead of two. However, the methods were largely the same, and the main findings were also the same across experiments.

Experimental Retrieval Practice Procedure:

Children first participated in a typical retrieval practice experimental procedure. The children first read a text passage about the sun twice—once by themselves and once along with the experimenter. Then, after a brief distraction task (solving math problems), the children practiced retrieval for some of the information in the text and reread other information (the retrieval practice and restudying conditions, respectively). During retrieval practice the children were given a cued-recall test; they saw sentences from the text passage with key words removed, and they were asked to remember the word. During restudy, the word was presented in bold font within the sentence.

For example, when the words Hydrogen and photosphere were assigned to the retrieval practice condition, they looked like this:

When the words Hydrogen and photosphere were assigned to the restudy condition, they looked like this:

One week later, the children completed final assessment tests (cued recall and multiple-choice in Experiment 1, and multiple-choice in Experiment 2).

Visual Word Decoding Ability

A few days after the final learning assessment was administered, the children performed a reading aloud task to assess visual word decoding ability. The children read Brazilian Portuguese nouns out loud (the experiment was conducted in Brazil) that were classified as regular, irregular, or pseudowords that were pronounceable but not true Brazilian Portuguese words. The children were instructed to read the words out loud, and they were scored on the number of words they pronounced correctly, and how quickly they responded.

Other Measures

In Experiment 2, the authors added other measures to assess cognitive ability. They attempted to measure reading comprehension, vocabulary skills, an estimated IQ, and working memory capacity.

In Experiment 1 with 6th graders, retrieval practice led to greater performance on the final learning assessment than restudying. Importantly, the benefit was similar across children with different word decoding abilities.

In Experiment 2 with 4th graders, the same was true! The size of the retrieval practice benefit, compared to restudying, was the same across children with different word decoding abilities.

Word decoding ability was positively correlated with final assessment test performance overall. When children had greater word decoding ability, their performance on the final assessment test was higher overall. Still, across word decoding ability, the size of the retrieval practice effects were comparable. This means that those with higher word decoding abilities generally did better in both conditions than those with lower word decoding abilities, but retrieval practice led to better performance compared to restudying across students. In other words, retrieval practice did not increase or decrease the performance gap between students with higher or lower verbal decoding ability. Retrieval practice seemed to work equally well.

In Experiment 2, the other measures included, such as reading comprehension, vocabulary skills, intelligence (estimated IQ), and working memory, all had no relationship to the size of the retrieval practice effect.

Taken together, the main conclusion from this research paper was that retrieval practice does seem to be effective for students with varying abilities!

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