How to Crack a Data Science Interview as a Fresher
- 1. How to Crack a Data Science Interview as a Fresher https://nareshit.com/courses/data-science-online-training
- 2. INTRODUCTION Challenge for freshers in the data science field Importance of preparation and strategy Purpose of this presentation: What key tips can lead to cracking an interview as a fresher?
- 3. KEY AREAS TO MASTER : Mathematics & Statistics : Probability, Hypothesis Testing, Linear Algebra. Data Structures & Algorithms: Arrays, Linked Lists, Sorting, Searching. Why it Matters : Employers expect foundational knowledge to solve real-world problems. https://nareshit.com/courses/data-science-online-training
- 4. PROGRAMMING SKILLS Python: Libraries – NumPy, pandas, scikit-learn. SQL: Essential for querying databases. Tools: Jupyter Notebooks, Git. Tip: Focus on writing clean, efficient code for data manipulation. https://nareshit.com/courses/data-science-online-training
- 5. Build a Portfolio: Data Cleaning Projects. Exploratory Data Analysis (EDA). Machine Learning Models. Showcasing Work: GitHub or personal portfolio. HANDS-ON EXPERIENCE WITH PROJECTS https://nareshit.com/courses/data-science-online-training
- 6. UNDERSTANDING MACHINE LEARNING ALGORITHMS SUPERVISED LEARNING: Linear/Logistic Regression, Decision Trees, k-NN. Unsupervised Learning: K-means Clustering, PCA. Model Evaluation: Accuracy, Precision, Recall, F1 score. https://nareshit.com/courses/data-science-online-training
- 7. Business Problem Solving. Data-Driven Decision Making. Feature Engineering and Model Selection. Approach: Use STAR Method (Situation, Task, Action, Result). PREPARING FOR CASE STUDIESWHAT TO EXPECT: https://nareshit.com/courses/data-science-online-training
- 8. SOFT SKILLS & BEHAVIORAL QUESTIONS Common Behavioral Questions : Teamwork and collaboration. Problem-solving under uncertainty. Adapting to new challenges. Tips: Use real examples from projects or internships. https://nareshit.com/courses/data-science-online-training
- 9. Data Science Tools: Cloud Platforms: AWS, Azure, GCP. Visualization Tools: Tableau, Power BI. Why it's Important: Practical knowledge of industry tools. FAMILIARITY WITH TOOLS & PLATFORMS https://nareshit.com/courses/data-science-online-training
- 10. Key Takeaways: Good grasping of basics. Practical projects and problem-solving ability. Ever learning and adaptable. Final Thought : With appropriate preparation, it is indeed the best time ever to face a data science interview as a fresher. Conclusion : https://nareshit.com/courses/data-science-online-training