Are you too old to change careers or go back to school?
NO. You’re never too old! Just for a moment flip it inside your head to someone else asking, would you tell a 35 year old to not even bother and to just either give up on their aspirations or stay in a job they hate? No you probably wouldn’t tell someone else they’re too old to bother.
To the 20 and 30 somethings who think it’s too late… well I have news for you, career and life is all about growth and change and experience!! You have 30-40 years of working ahead of you! You barely have started. Get off the socials that make you think you need to be killing it by age 22, that’s just not reality.
So go out there and get the degree at 43, or change careers at 25 or 55!!
Jobadvisor
Absolutely not! It's fantastic that you're challenging the idea that there's an age limit for career changes or returning to school. Your perspective is spot on: you'd rarely tell someone else they're too old to pursue their dreams, so why apply that limiting belief to yourself?
Life and careers are all about continuous growth, learning, and adaptation. Whether you're in your 20s, 30s, 40s, 50s, or beyond, you likely have many years of work and personal development ahead of you. The idea that you need to have everything figured out by your early twenties is a social media-fueled myth that doesn't reflect the reality of most people's journeys.
So, if you're considering getting a degree at 43, making a career pivot at 25, or starting fresh at 55, go for it! Your unique experiences and fresh perspective will be valuable assets, no matter your age.
Need Career Advice as a 3rd-Year CSE Student (Data Science vs. Business Analyst vs. Supply Chain) ?
Hey everyone,
I'm a 3rd-year BTech CSE student at a lower-tier government university, and I'm feeling lost about my career path. I need to pick a direction soon but don’t have mentors to guide me.
I’m considering:
Data Science (ML, Python, stats)
Business Analyst (SQL, communication, problem-solving)
Supply Chain Automation (logistics + tech integration)
My Questions:
Which field has better opportunities for someone from a non-top-tier college?
Can I switch later (e.g., start as a business Analyst → move to Data Science)?
What are the must-learn skills for each role?
I’m ready to put in the work but need some clarity. Any advice, personal experiences, or resources would be super helpful!
(Thanks in advance—really appreciate it!)
Jobadvisor
It's commendable that you're thinking strategically about your career path as a 3rd-year CSE student, especially without direct mentors. Let's break down your options and provide some guidance, keeping in mind your background from a lower-tier government university in India.
It's commendable that you're thinking strategically about your career path as a 3rd-year CSE student, especially without direct mentors. Let's break down your options and provide some guidance, keeping in mind your background from a lower-tier government university in India.
1. Which field has better opportunities for someone from a non-top-tier college?
All three fields—Data Science, Business Analyst, and Supply Chain Automation—have significant opportunities in India, and your university tier is less of a barrier than your demonstrable skills and projects. Here's a comparative view:
Data Science:
Demand: The demand for data scientists in India is booming, with NASSCOM projecting a 300% rise between 2022 and 2030.1 Many industries (healthcare, banking, retail, manufacturing, agriculture) are rapidly adopting data science.2
Competition: While demand is high, so is competition, especially for entry-level roles. Companies often prefer candidates with strong portfolios showcasing practical application of ML, Python, and statistics.
Advantage for you: If you can build a strong portfolio and demonstrate hands-on experience, your university tier becomes less critical.
Business Analyst:
Demand: The business analytics market in India is also experiencing significant growth, driven by the need for data-driven decision-making.3 There's a "massive gap" between business analyst and data scientist vacancies, with more business analyst roles available.
Entry Barrier: This role often has a slightly lower technical entry barrier than pure data science, as it heavily relies on communication and problem-solving alongside SQL skills.
Advantage for you: Your CSE background gives you a technical edge over business graduates. If you pair that with strong communication and analytical thinking, you can be a strong candidate.
Supply Chain Automation:
Demand: India's supply chain management market is projected to witness significant growth, driven by digital transformation, rising operational costs, and increasing customer expectations for faster delivery.4 This translates to a growing need for professionals who can integrate technology into logistics.
Niche Expertise: This is a more specialized field. While there might be fewer sheer numbers of roles compared to general data science or business analysis, the demand for this specific skill set is increasing, which can lead to less competition within this niche.
Advantage for you: Your CSE background is a direct fit for the "automation" aspect. If you can combine that with an understanding of logistics, you'll be highly valuable.
Overall:
From a non-top-tier college, Business Analyst might offer more readily available entry-level opportunities due to the broader scope and slightly less emphasis on advanced technical depth compared to Data Science. However, Data Science offers higher earning potential in the long run if you excel. Supply Chain Automation is a strong niche with growing demand, and your CSE background is highly relevant.
Your success will largely depend on your projects, certifications, and how well you can articulate your skills and passion, regardless of your college.
All three fields—Data Science, Business Analyst, and Supply Chain Automation—have significant opportunities in India, and your university tier is less of a barrier than your demonstrable skills and projects. Here's a comparative view:
Data Science:
Demand: The demand for data scientists in India is booming, with NASSCOM projecting a 300% rise between 2022 and 2030.
1 Many industries (healthcare, banking, retail, manufacturing, agriculture) are rapidly adopting data science.2 Competition: While demand is high, so is competition, especially for entry-level roles. Companies often prefer candidates with strong portfolios showcasing practical application of ML, Python, and statistics.
Advantage for you: If you can build a strong portfolio and demonstrate hands-on experience, your university tier becomes less critical.
Business Analyst:
Demand: The business analytics market in India is also experiencing significant growth, driven by the need for data-driven decision-making.
3 There's a "massive gap" between business analyst and data scientist vacancies, with more business analyst roles available.Entry Barrier: This role often has a slightly lower technical entry barrier than pure data science, as it heavily relies on communication and problem-solving alongside SQL skills.
Advantage for you: Your CSE background gives you a technical edge over business graduates. If you pair that with strong communication and analytical thinking, you can be a strong candidate.
Supply Chain Automation:
Demand: India's supply chain management market is projected to witness significant growth, driven by digital transformation, rising operational costs, and increasing customer expectations for faster delivery.
4 This translates to a growing need for professionals who can integrate technology into logistics.Niche Expertise: This is a more specialized field. While there might be fewer sheer numbers of roles compared to general data science or business analysis, the demand for this specific skill set is increasing, which can lead to less competition within this niche.
Advantage for you: Your CSE background is a direct fit for the "automation" aspect. If you can combine that with an understanding of logistics, you'll be highly valuable.
Overall:
From a non-top-tier college, Business Analyst might offer more readily available entry-level opportunities due to the broader scope and slightly less emphasis on advanced technical depth compared to Data Science. However, Data Science offers higher earning potential in the long run if you excel. Supply Chain Automation is a strong niche with growing demand, and your CSE background is highly relevant.
Your success will largely depend on your projects, certifications, and how well you can articulate your skills and passion, regardless of your college.
2. Can I switch later (e.g., start as a Business Analyst → move to Data Science)?
Absolutely, yes! This is a very common and often recommended path.
Business Analyst to Data Scientist: This is a natural progression. As a Business Analyst, you'll gain invaluable domain knowledge, understand business problems, and work with data. You'll likely be proficient in SQL and data visualization tools. To transition to Data Science, you'll need to deepen your technical skills in:
Advanced Python/R: For more complex data manipulation, statistical modeling, and machine learning.
Machine Learning Algorithms: Understanding their theory and application.
Statistical Modeling: A deeper dive than what's typically required for a BA.
Big Data Technologies: (Hadoop, Spark) if working with very large datasets.
Building a Data Science Portfolio: Showcasing end-to-end projects.
Other Switches:
Data Science to Business Analyst: Easier switch, as you'd already have the technical skills. You'd need to hone your communication, stakeholder management, and business acumen.
Supply Chain Automation to Data Science/Business Analyst: Also possible. Your understanding of logistics data and systems would be a huge asset. You'd need to acquire the core data science or business analysis skills as outlined.
Starting as a Business Analyst can give you a strong foundation in understanding business needs and translating them into technical requirements, which is a crucial skill for a Data Scientist.
Absolutely, yes! This is a very common and often recommended path.
Business Analyst to Data Scientist: This is a natural progression. As a Business Analyst, you'll gain invaluable domain knowledge, understand business problems, and work with data. You'll likely be proficient in SQL and data visualization tools. To transition to Data Science, you'll need to deepen your technical skills in:
Advanced Python/R: For more complex data manipulation, statistical modeling, and machine learning.
Machine Learning Algorithms: Understanding their theory and application.
Statistical Modeling: A deeper dive than what's typically required for a BA.
Big Data Technologies: (Hadoop, Spark) if working with very large datasets.
Building a Data Science Portfolio: Showcasing end-to-end projects.
Other Switches:
Data Science to Business Analyst: Easier switch, as you'd already have the technical skills. You'd need to hone your communication, stakeholder management, and business acumen.
Supply Chain Automation to Data Science/Business Analyst: Also possible. Your understanding of logistics data and systems would be a huge asset. You'd need to acquire the core data science or business analysis skills as outlined.
Starting as a Business Analyst can give you a strong foundation in understanding business needs and translating them into technical requirements, which is a crucial skill for a Data Scientist.
3. What are the must-learn skills for each role?
Here's a breakdown of essential skills:
Here's a breakdown of essential skills:
Data Science (ML, Python, Stats)
Technical Skills:
Programming Languages:
Python: Absolutely essential. Libraries like Pandas (data manipulation), NumPy (numerical computing), Scikit-learn (machine learning), Matplotlib & Seaborn (data visualization), TensorFlow/PyTorch (deep learning).
R: (Optional but good for statistical analysis and visualization, especially in academia or specific domains).
SQL: Crucial for querying and managing databases to extract data.
Statistics & Mathematics:
Probability, Hypothesis Testing, Regression Analysis.
Linear Algebra, Calculus (foundational for understanding ML algorithms).5
Machine Learning:
Understanding of supervised (regression, classification), unsupervised (clustering), and reinforcement learning concepts.
Knowledge of common algorithms: Linear Regression, Logistic Regression, Decision Trees, Random Forests, Support Vector Machines, Neural Networks.
Data Manipulation & Cleaning (Data Wrangling):
Handling missing values, outliers, data transformation.
Data Visualization:
Tools like Matplotlib, Seaborn, Tableau, Power BI, ggplot2 (R).
Big Data Technologies (Good to have, especially for larger companies):
Hadoop, Spark.
Cloud Platforms (Good to have):
AWS, Azure, GCP (for deploying models and working with cloud data).
Soft Skills:
Problem-solving: Ability to frame business problems as data science problems.
Critical Thinking: Interpreting results and understanding limitations.
Communication & Storytelling: Explaining complex technical findings to non-technical stakeholders.
Curiosity & Continuous Learning: The field is rapidly evolving.
Technical Skills:
Programming Languages:
Python: Absolutely essential. Libraries like Pandas (data manipulation), NumPy (numerical computing), Scikit-learn (machine learning), Matplotlib & Seaborn (data visualization), TensorFlow/PyTorch (deep learning).
R: (Optional but good for statistical analysis and visualization, especially in academia or specific domains).
SQL: Crucial for querying and managing databases to extract data.
Statistics & Mathematics:
Probability, Hypothesis Testing, Regression Analysis.
Linear Algebra, Calculus (foundational for understanding ML algorithms).
5
Machine Learning:
Understanding of supervised (regression, classification), unsupervised (clustering), and reinforcement learning concepts.
Knowledge of common algorithms: Linear Regression, Logistic Regression, Decision Trees, Random Forests, Support Vector Machines, Neural Networks.
Data Manipulation & Cleaning (Data Wrangling):
Handling missing values, outliers, data transformation.
Data Visualization:
Tools like Matplotlib, Seaborn, Tableau, Power BI, ggplot2 (R).
Big Data Technologies (Good to have, especially for larger companies):
Hadoop, Spark.
Cloud Platforms (Good to have):
AWS, Azure, GCP (for deploying models and working with cloud data).
Soft Skills:
Problem-solving: Ability to frame business problems as data science problems.
Critical Thinking: Interpreting results and understanding limitations.
Communication & Storytelling: Explaining complex technical findings to non-technical stakeholders.
Curiosity & Continuous Learning: The field is rapidly evolving.
Business Analyst (SQL, Communication, Problem-Solving)
Technical Skills:
SQL: Essential for querying databases and extracting data.
Spreadsheet Software:
Microsoft Excel: Advanced proficiency for data analysis, modeling, and reporting.
Business Intelligence (BI) & Data Visualization Tools:
Tableau, Power BI, QlikView.
Basic Understanding of Databases: Relational databases, data warehousing.
Understanding of SDLC (Software Development Life Cycle): Especially if working on software projects.
Familiarity with Project Management Tools: Asana, Trello, Jira.
Basic understanding of Machine Learning/AI concepts (Emerging Trend): To understand what data scientists can achieve and how to integrate AI/ML into business processes.
Soft Skills:
Communication: Excellent verbal and written communication, active listening, presenting findings clearly. (Crucial for bridging the gap between business and IT).
Problem-solving & Critical Thinking: Identifying root causes, analyzing scenarios, proposing solutions.
Analytical Skills: Ability to assess and interpret information, make data-driven recommendations.
Stakeholder Management & Negotiation: Working with diverse teams and managing expectations.
Domain Knowledge: Understanding the specific industry or business processes you're analyzing.
Adaptability & Continuous Learning: Business processes and tools evolve.
Technical Skills:
SQL: Essential for querying databases and extracting data.
Spreadsheet Software:
Microsoft Excel: Advanced proficiency for data analysis, modeling, and reporting.
Business Intelligence (BI) & Data Visualization Tools:
Tableau, Power BI, QlikView.
Basic Understanding of Databases: Relational databases, data warehousing.
Understanding of SDLC (Software Development Life Cycle): Especially if working on software projects.
Familiarity with Project Management Tools: Asana, Trello, Jira.
Basic understanding of Machine Learning/AI concepts (Emerging Trend): To understand what data scientists can achieve and how to integrate AI/ML into business processes.
Soft Skills:
Communication: Excellent verbal and written communication, active listening, presenting findings clearly. (Crucial for bridging the gap between business and IT).
Problem-solving & Critical Thinking: Identifying root causes, analyzing scenarios, proposing solutions.
Analytical Skills: Ability to assess and interpret information, make data-driven recommendations.
Stakeholder Management & Negotiation: Working with diverse teams and managing expectations.
Domain Knowledge: Understanding the specific industry or business processes you're analyzing.
Adaptability & Continuous Learning: Business processes and tools evolve.
Supply Chain Automation (Logistics + Tech Integration)
Technical Skills:
Programming:
Python: For scripting automation, data analysis, and integrating systems.6
SQL: For managing and extracting data from supply chain databases.
Understanding of Supply Chain Management (SCM) Principles:
Logistics, warehousing, inventory management, procurement, demand planning, distribution.
SCM Software Knowledge:
Transportation Management Systems (TMS), Warehouse Management Systems (WMS), Enterprise Resource Planning (ERP) systems (e.g., SAP, Oracle).
Data Analysis & Interpretation:
Using tools like Excel, specialized SCM software, and potentially BI tools to analyze supply chain data.
Automation Technologies:
Robotics Process Automation (RPA), IoT (Internet of Things) for tracking, potentially AI/ML for predictive analytics in demand forecasting or route optimization.
Cloud Computing Basics: Understanding how cloud platforms can host SCM solutions.
System Integration: Knowledge of APIs and how different systems communicate.
Soft Skills:
Strategic Thinking: Anticipating trends, identifying improvement areas in the supply chain.
Problem-solving: Quickly addressing disruptions, optimizing processes.
Communication & Negotiation: Collaborating with suppliers, customers, and internal teams.
Project Management: Managing automation projects, timelines, and budgets.
Adaptability: The supply chain is dynamic and prone to unexpected events.
Customer Service Orientation: Focusing on timely deliveries and service quality.
Process Improvement Mindset: Constantly looking for efficiencies.
Technical Skills:
Programming:
Python: For scripting automation, data analysis, and integrating systems.
6 SQL: For managing and extracting data from supply chain databases.
Understanding of Supply Chain Management (SCM) Principles:
Logistics, warehousing, inventory management, procurement, demand planning, distribution.
SCM Software Knowledge:
Transportation Management Systems (TMS), Warehouse Management Systems (WMS), Enterprise Resource Planning (ERP) systems (e.g., SAP, Oracle).
Data Analysis & Interpretation:
Using tools like Excel, specialized SCM software, and potentially BI tools to analyze supply chain data.
Automation Technologies:
Robotics Process Automation (RPA), IoT (Internet of Things) for tracking, potentially AI/ML for predictive analytics in demand forecasting or route optimization.
Cloud Computing Basics: Understanding how cloud platforms can host SCM solutions.
System Integration: Knowledge of APIs and how different systems communicate.
Soft Skills:
Strategic Thinking: Anticipating trends, identifying improvement areas in the supply chain.
Problem-solving: Quickly addressing disruptions, optimizing processes.
Communication & Negotiation: Collaborating with suppliers, customers, and internal teams.
Project Management: Managing automation projects, timelines, and budgets.
Adaptability: The supply chain is dynamic and prone to unexpected events.
Customer Service Orientation: Focusing on timely deliveries and service quality.
Process Improvement Mindset: Constantly looking for efficiencies.
Advice for a Student from a Non-Top-Tier College:
Build a Strong Portfolio: This is your biggest differentiator. For Data Science, this means Kaggle competitions, personal projects using real-world datasets, and open-source contributions. For Business Analyst, case studies where you analyze a business problem and propose solutions based on data. For Supply Chain Automation, projects demonstrating how you've used tech to optimize a hypothetical or real logistics process.
Online Courses & Certifications: Leverage platforms like Coursera, edX, Udemy, DataCamp, Udacity to gain specialized skills and certifications.7 These are widely recognized.
Networking: Attend online webinars, join LinkedIn groups, connect with professionals in your target fields. Informational interviews can provide invaluable insights and potential leads.
Internships: Seek out internships aggressively. Practical experience is highly valued, especially for non-top-tier graduates. Even unpaid internships or working on projects for startups can give you a significant edge.
Focus on Fundamentals: Regardless of the path, a strong grasp of programming, data structures, algorithms, and SQL (given your CSE background) is universally beneficial.
Develop Strong Communication Skills: This is vital for all three roles, especially for Business Analysts. Practice presenting your ideas clearly and concisely.
You're in a great position as a 3rd-year student to start shaping your career. Pick one or two areas that genuinely excite you, dive deep into the "must-learn" skills, and start building practical projects. Your dedication and demonstrable abilities will open doors. Good luck!
Build a Strong Portfolio: This is your biggest differentiator. For Data Science, this means Kaggle competitions, personal projects using real-world datasets, and open-source contributions. For Business Analyst, case studies where you analyze a business problem and propose solutions based on data. For Supply Chain Automation, projects demonstrating how you've used tech to optimize a hypothetical or real logistics process.
Online Courses & Certifications: Leverage platforms like Coursera, edX, Udemy, DataCamp, Udacity to gain specialized skills and certifications.
7 These are widely recognized.Networking: Attend online webinars, join LinkedIn groups, connect with professionals in your target fields. Informational interviews can provide invaluable insights and potential leads.
Internships: Seek out internships aggressively. Practical experience is highly valued, especially for non-top-tier graduates. Even unpaid internships or working on projects for startups can give you a significant edge.
Focus on Fundamentals: Regardless of the path, a strong grasp of programming, data structures, algorithms, and SQL (given your CSE background) is universally beneficial.
Develop Strong Communication Skills: This is vital for all three roles, especially for Business Analysts. Practice presenting your ideas clearly and concisely.
You're in a great position as a 3rd-year student to start shaping your career. Pick one or two areas that genuinely excite you, dive deep into the "must-learn" skills, and start building practical projects. Your dedication and demonstrable abilities will open doors. Good luck!
I’m 21, took two gap years. Do y’all think I ruined everything?
I graduated with a bachelor’s in psychology last year 2024 but I’ve basically done nothing since then. Most of the past year went by in a haze of depression, confusion and feeling of completely being lost. I didn’t know what to do next with my life, I still don’t fully know. And now I’m taking another gap year to prepare for the M.Des (Master of Design) exam.
I’m scared. I feel like I’ve wasted two years that could’ve been spent building a career or gaining experience. Everyone around me seems to be moving forward and I feel stuck in the same place. Even though I’ve recently started learning graphic design and creating artwork it feels like I’m late to everything.
I know 21 isn’t old. But these two gap years feel like a weight I can’t shake off. I keep thinking, “Did I ruin my chances? Will this gap define me forever?”
If anyone has taken gap years, changed paths or just felt completely lost. I’d love to hear from you.
Jobadvisor
It's completely understandable to feel overwhelmed and uncertain right now. Many people experience similar feelings, especially in their early twenties when there's so much pressure to have everything figured out. Let's address your concerns directly.
I graduated with a bachelor’s in psychology last year 2024 but I’ve basically done nothing since then. Most of the past year went by in a haze of depression, confusion and feeling of completely being lost. I didn’t know what to do next with my life, I still don’t fully know. And now I’m taking another gap year to prepare for the M.Des (Master of Design) exam.
I’m scared. I feel like I’ve wasted two years that could’ve been spent building a career or gaining experience. Everyone around me seems to be moving forward and I feel stuck in the same place. Even though I’ve recently started learning graphic design and creating artwork it feels like I’m late to everything.
I know 21 isn’t old. But these two gap years feel like a weight I can’t shake off. I keep thinking, “Did I ruin my chances? Will this gap define me forever?”
If anyone has taken gap years, changed paths or just felt completely lost. I’d love to hear from you.
Jobadvisor
It's completely understandable to feel overwhelmed and uncertain right now. Many people experience similar feelings, especially in their early twenties when there's so much pressure to have everything figured out. Let's address your concerns directly.
You Haven't Ruined Anything
First and foremost, you absolutely haven't ruined everything. Two gap years, especially at your age, are not a career-ending mistake. In the grand scheme of a decades-long career, two years is a very small blip. Many successful individuals have taken time off, changed career paths, or started later in life. What feels like a significant delay now will likely be a footnote in your professional journey.
First and foremost, you absolutely haven't ruined everything. Two gap years, especially at your age, are not a career-ending mistake. In the grand scheme of a decades-long career, two years is a very small blip. Many successful individuals have taken time off, changed career paths, or started later in life. What feels like a significant delay now will likely be a footnote in your professional journey.
The Value of Your Gap Years
While it might not feel like it, even the "haze of depression, confusion, and feeling completely lost" can lead to valuable insights. It sounds like this period has prompted a significant self-reflection, leading you to explore graphic design and artwork, and ultimately, to pursue a Master of Design. This clarity and new direction might not have happened if you had immediately jumped into something you weren't passionate about after your psychology degree.
Consider these aspects:
Self-Discovery: These years have been crucial for understanding what you don't want and what you do want. That's invaluable knowledge that many people don't gain until much later in life.
Skill Development: You've actively started learning graphic design and creating artwork. These are tangible skills that will directly contribute to your M.Des application and future career.
Mental Well-being: Addressing your depression and confusion, even if it felt like a struggle, is essential. Pushing yourself into a career while battling mental health challenges can lead to burnout and further distress. Taking this time, even if difficult, allowed you to start a new path from a more stable place.
While it might not feel like it, even the "haze of depression, confusion, and feeling completely lost" can lead to valuable insights. It sounds like this period has prompted a significant self-reflection, leading you to explore graphic design and artwork, and ultimately, to pursue a Master of Design. This clarity and new direction might not have happened if you had immediately jumped into something you weren't passionate about after your psychology degree.
Consider these aspects:
Self-Discovery: These years have been crucial for understanding what you don't want and what you do want. That's invaluable knowledge that many people don't gain until much later in life.
Skill Development: You've actively started learning graphic design and creating artwork. These are tangible skills that will directly contribute to your M.Des application and future career.
Mental Well-being: Addressing your depression and confusion, even if it felt like a struggle, is essential. Pushing yourself into a career while battling mental health challenges can lead to burnout and further distress. Taking this time, even if difficult, allowed you to start a new path from a more stable place.
Comparing Yourself to Others
It's natural to compare yourself to peers, especially when it feels like they're hitting traditional milestones. However, everyone's journey is unique. Your friends might be in roles they'll eventually leave, or they might be facing their own anxieties you don't see. Focus on your own path and progress rather than external timelines. The idea of a "linear" career path is increasingly outdated.
It's natural to compare yourself to peers, especially when it feels like they're hitting traditional milestones. However, everyone's journey is unique. Your friends might be in roles they'll eventually leave, or they might be facing their own anxieties you don't see. Focus on your own path and progress rather than external timelines. The idea of a "linear" career path is increasingly outdated.
Your New Path Forward
The fact that you're actively preparing for the M.Des exam and engaging with graphic design and artwork shows tremendous initiative and resilience. This is a positive and proactive step. Your psychology background, combined with design, could even offer a unique perspective in the design field, especially in areas like user experience (UX) design, where understanding human behavior is key.
The fact that you're actively preparing for the M.Des exam and engaging with graphic design and artwork shows tremendous initiative and resilience. This is a positive and proactive step. Your psychology background, combined with design, could even offer a unique perspective in the design field, especially in areas like user experience (UX) design, where understanding human behavior is key.
Moving Ahead
Embrace the Learning: View these two years not as wasted time, but as a period of personal growth and redirection.
Focus on Your Goals: Keep your focus on preparing for the M.Des and continuing to build your design portfolio.
Connect with Others: Reach out to people in the design field. You might be surprised to find how many have non-traditional backgrounds.
Be Kind to Yourself: The self-criticism you're experiencing is common. Practice self-compassion and acknowledge the courage it takes to pivot and pursue a new passion.
Many people have taken gap years, changed paths, or felt completely lost. What truly matters is what you do with the knowledge and experience gained during that time. You're on a new path, and that's something to be proud of, not ashamed of.
Do you want to talk more about specific ways to leverage your psychology background in design, or perhaps strategies for preparing for the M.Des exam?
Embrace the Learning: View these two years not as wasted time, but as a period of personal growth and redirection.
Focus on Your Goals: Keep your focus on preparing for the M.Des and continuing to build your design portfolio.
Connect with Others: Reach out to people in the design field. You might be surprised to find how many have non-traditional backgrounds.
Be Kind to Yourself: The self-criticism you're experiencing is common. Practice self-compassion and acknowledge the courage it takes to pivot and pursue a new passion.
Many people have taken gap years, changed paths, or felt completely lost. What truly matters is what you do with the knowledge and experience gained during that time. You're on a new path, and that's something to be proud of, not ashamed of.
Do you want to talk more about specific ways to leverage your psychology background in design, or perhaps strategies for preparing for the M.Des exam?