Golla Anand’s Journey from Fresher to Python Developer

Golla Anand’s journey highlights how a fresher from a non-coding background successfully transitioned into a Python Developer through consistent learning and guided training. His story reflects the importance of dedication, practical practice, and structured upskilling in building a tech career.

Priyanka BR Priyanka BR
May 4, 2026 Updated: May 13, 2026
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Golla Anand’s Journey from Fresher to Python Developer
Datamites AI Engineer course success story by Golla Anand

Have you ever wondered how a fresher from an Information Technology background can step into the world of Artificial Intelligence and Data Science without prior coding experience? Meet Golla Anand, who turned his interest in technology into a growing career path by taking the right learning approach, consistent practice, and structured guidance.

His journey was not without challenges. Coming from a non-AI background, he initially struggled with Python programming and machine learning concepts. However, with continuous learning, practice, and project-based exposure, he gradually built strong technical skills. The turning point in his journey was joining DataMites, where he gained hands-on experience through capstone and live projects that helped him understand real-world AI applications.

Today, Golla Anand has secured a role as a Python Developer, showing how consistent effort and the right training can help a beginner move toward a strong technical career.

How Golla Anand Started His AI Journey with DataMites

Golla Anand’s journey reflects how structured learning and the right guidance can help shape a strong technical career. With consistent effort and hands-on training at DataMites, he was able to build a solid foundation in AI-related skills and move forward in his professional path as a Python Developer.

1. How did you actually get introduced to AI and Data Science?

Hi, my name is Anand. I came into the field of AI and data science through a reference from a friend who was already studying data science, and that is how I developed interest in this domain. Since I had completed my B.Tech in Information Technology, I felt it was a good direction for my career, so I decided to explore and join structured training in data science. I have secured a position as a Python Developer at Feather Soft Solutions.

2. Did you already know Python or programming before starting?

No, I had no prior knowledge at all. I started as a complete beginner. Everything from Python basics to machine learning concepts was new to me, and I learned it step by step through the training program.

3. Which area of data science and AI did you enjoy the most?

Machine learning was my favorite part. I felt it is the core of data science, and most of the important concepts are connected to it. So I focused more on understanding machine learning properly.

4. How was your experience with projects during training?

I completed four capstone projects and one live project at DataMites. The live project was more challenging as it involved real-world data on incident priority prediction with SQL-based data access, unlike capstone projects which used ready-made datasets.

5. What was different between capstone and live projects?

In capstone projects, we usually get ready-made datasets to practice. But in the live project, we had to access data through SQL login, and it felt more realistic. It gave me exposure to how actual industry projects work.

6. How did you manage your daily learning routine?

I used to spend around two hours daily practicing. I also made notes after every class and revised them in the morning. Along with live classes, I regularly watched recorded sessions, which helped me understand topics better.

7. How useful were recorded classes for your learning?

Recorded classes were very helpful. Sometimes I didn’t fully understand a topic in live class, so I would rewatch the recordings. It helped me strengthen my basics and clear doubts at my own pace.

8. What kind of interview preparation did you go through?

Mock interviews mostly covered basic topics like Python, NumPy, and simple machine learning algorithms. They were not very difficult but helped me understand how interviews are structured and what basics I need to be strong in.

9. What is your suggestion for students who want to enter AI?

I would suggest focusing more on machine learning and practicing daily. Don’t depend only on live classes. Recorded sessions, revision, and hands-on practice are equally important. Also, working on live projects gives much better industry understanding compared to only capstone projects.

10. If you had to summarize your learning experience, what would you say?

I started with zero knowledge and gradually built my skills through consistent practice and training. Data science is not something you learn in a day. It needs patience, repetition, and real project experience. If someone follows the process properly, they can definitely build a strong foundation in this field.

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Key AI Career Insights from Golla Anand’s Journey at DataMites

Golla Anand’s journey gives simple but strong insights for anyone starting a career in Artificial Intelligence and Data Science:

  • Golla Anand started from a non-coding background and proved that beginners can learn AI and data science with proper guidance and consistent practice.
  • He faced initial AI challenges with Python, but regular learning and practice helped him build strong fundamentals over time.
  • His focus on Python and Machine Learning helped him align with industry requirements and improve his technical skills step by step.
  • At DataMites, working on capstone projects and a live project gave him practical exposure to real-world data problems.
  • The live project experience, especially incident priority prediction using SQL data access, helped him understand real industry workflows better.
  • Daily practice, revision of notes, and watching recorded sessions helped him strengthen his understanding and improve consistency.
  • Mentor support and structured training played an important role in clearing doubts and keeping his learning on track.
  • Overall, Golla Anand’s journey shows that with consistent effort, guided training, and project experience, beginners can build strong foundations in Artificial Intelligence and Data Science.

Golla Anand’s journey clearly reflects how the right combination of structured learning, consistent practice, and real-world exposure can shape a successful career in Artificial Intelligence. From building a strong foundation through Python Training, machine learning, and AI concepts at DataMites Training, he gradually strengthened both his technical understanding and practical skills. Along with this, hands-on exposure through capstone and live projects helped him apply what he learned in real scenarios, improving his confidence and problem-solving ability.

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DataMites Institute offers a structured 9-month Artificial Intelligence program designed to develop job-ready skills through hands-on tools, real-time projects, and a strong focus on responsible AI practices. The program provides multiple learning paths such as AI Engineer, AI Specialist, AI for Product Managers, AI Foundation, and Certified NLP Professional, allowing learners to choose based on their career goals. With globally recognized certifications from IABAC and NASSCOM FutureSkills, the training helps learners gain practical knowledge and confidence to work in real-world AI and machine learning roles.

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