Path-Builder Foundation’s Post

"Thrilled to share that I've successfully completed 6 months as a Data Analyst Intern at Ai Variant!🚀 During this enriching experience, I delved into the world of data, honing skills in data analysis, visualization, and statistical methods. Collaborating with a dynamic team, I contributed to impactful projects, gaining hands-on experience in cleaning, preprocessing, and validating data. 📊 I had the opportunity to create and maintain data pipelines, conduct exploratory data analysis, and assist in building predictive models. Leveraging tools such as Microsoft Excel, SQL, Power Bi, Tableau, Apache Hadoop and refining my proficiency in Python, R, I'm proud of the skills I've developed in a real-world, fast-paced environment. 🔍 Grateful for the mentorship and support I received, paving the way for my growth in this field. Excited to take the next steps in my data analytics journey! 🌐 #DataAnalyst #InternshipExperience #DataAnalytics #ProfessionalGrowth"

Top Mistakes to Avoid in Your Data Science Interview 🚫 🗓️ Early-Bird Offer on My Live Weekday Data Science Projects-Data Science Focused Program with Internship, To learn more, Whatsapp Us at: +919347125815 / +919121516181 #DataScience #InterviewTips #DataScienceInterview #CareerTips #InterviewMistakes #JobSearch #DataScienceCareers #MachineLearning #AI #DataAnalysis #TechInterviews #InterviewPreparation #CareerAdvice #Analytics #DataScienceJobs #DataScienceSkills #JobHunt #CodingInterviews #InterviewSuccess

Top Mistakes to Avoid in Your Data Science Interview 🚫 🗓️ Early-Bird Offer on My Live Weekday Data Science Projects-Data Science Focused Program with Internship, To learn more, Whatsapp Us at: +919347125815 / +919121516181 #DataScience #InterviewTips #DataScienceInterview #CareerTips #InterviewMistakes #JobSearch #DataScienceCareers #MachineLearning #AI #DataAnalysis #TechInterviews #InterviewPreparation #CareerAdvice #Analytics #DataScienceJobs #DataScienceSkills #JobHunt #CodingInterviews #InterviewSuccess

Data Cleaning is one of the most important steps in ensuring the quality of Data for further processing it. Whenevery a Data Analyst or Data Scientist wants to extract insights from the data, he/she should make sure that the data is clean, accurate, and ready for the process, otherwise, the insights generated from the data can have bad impacts. I found this book for Data Cleaning which is a must-read resource for anyone working with data. It shows all the data cleaning techniques in the best way with detailed explanation, relevant examples, and scenarios. I highly recommend this book for anyone working with data. Make sure to read this book and leave your thoughts in the comments section below. ----------------------------------------------------------- We provide information, tutorials, projects, internships, and much more about Data Analytics, Data Engineering, and Data Science fields on the Awesome Data channel. If you are interested, you may check it out. Channel Link: https://lnkd.in/ddWXfa9N #Data #DataAnalytics #DataEngineering #DataScience #DataCleaning #DataWrangling #DataProcessing #KnowledgeSharing #MustReadResource

Data Science Task - 2: Program Overview: Unemployment Analysis 1. Problem Statement: Analyze the impact of Covid-19 on unemployment rates, focusing on regional trends and changes over time. 2. Approach: Data Loading: Load the unemployment dataset from a CSV file using pandas. Data Cleaning: Check for and handle missing values and duplicate entries. Data Transformation: Rename columns for clarity and ensure correct data types. Data Exploration: Use descriptive statistics and visualizations to understand the dataset. Regional Analysis: Investigate unemployment rates by region, identifying the most affected areas. Employment Analysis: Explore the relationship between employment and unemployment rates. Time Analysis: Analyze how unemployment rates have changed over time. Visualization: Create various plots (bar graphs, line graphs, histograms, etc.) to visualize the data. 3. Execution: Load the dataset and perform data cleaning and transformation. Explore the data through descriptive statistics and visualizations. Analyze regional trends, employment rates, and changes over time. Use matplotlib and seaborn for plotting. 4. Result: Gain insights into the impact of Covid-19 on unemployment rates, highlighting regional disparities and trends over time. Oasis Infobyte #oasisinfobyte #DataScience #Internship

From an ML intern to a Lead Data Scientist,  Here is how I switched 4 companies 🔽 🔹 𝐋𝐞𝐚𝐫𝐧𝐞𝐝 𝐒𝐐𝐋 𝐚𝐧𝐝 𝐏𝐲𝐭𝐡𝐨𝐧: I sharpened my SQL and Python skills by solving real-world data problems with complex queries and scripts. 🔹 𝐏𝐫𝐞𝐩𝐚𝐫𝐞𝐝 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐒𝐭𝐨𝐫𝐢𝐞𝐬: I detailed my projects in interviews, focusing on the problem, data, methods, and outcomes. 🔹 𝐀𝐜𝐞𝐝 𝐁𝐞𝐡𝐚𝐯𝐢𝐨𝐫𝐚𝐥 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬: I used the STAR method to answer behavioral questions effectively. #Protip for aspiring data scientists → Develop a practice routine and regularly evaluate your progress. If you are stuck at some point, reach out to senior data scientists for feedback. There are also platforms like Preplaced where you can connect with experienced data scientists or analysts for personalized guidance. Book a FREE doubt-clearing session with them here - https://lnkd.in/g3pUB_BN These data mentors will take complete responsibility for your growth—upskilling, interview preparation, building projects, resume optimization, you name it. They will support you till you secure your ideal data role. 💫 Try it out! #careerjourney #datascience #collab #preplacedcollab #jobswitch #careertransition

Why do I want to become a data scientist? My journey into data science starts with my love for numbers, which grew during my Bachelor's degree in Statistics. Moving into data science is challenging, especially since I didn't know much about programming at first. My background in statistics helped me with analysis, but learning to code felt like climbing a mountain. Despite the challenges, I am determined to keep going. With hard work and dedication, I have learned Python, SQL, and Power BI. Now, I analyze data with these tools and enjoy finding insights. My next goal is to master machine learning and deep learning, and I am working hard to achieve that. I am always looking for internships and entry-level jobs to use my skills in real-world situations. I believe that persistence and continuous learning are the keys to success in this field. Every challenge I overcome brings me closer to my dream, and I am committed to this journey with determination. #DataScience #Statistics #Python #SQL #PowerBI #MachineLearning #DeepLearning #LearningJourney #CareerGrowth #Persistence #Passion

Journey into Data Science: Turning Data into Insights! As a Data Science student, I’m continuously amazed at how data can shape the future of industries. Every dataset tells a story, and I’m passionate about uncovering those insights to solve real-world problems. Over the past few months, I’ve worked on various projects where I utilized tools like Python, SQL, and Power BI to perform data analysis and predictive modeling. One of my recent projects involved analyzing a large customer dataset to identify patterns in purchasing behavior, which helped me better understand the power of machine learning algorithms in driving business decisions. I’m excited to keep learning, collaborating, and applying my skills to help organizations leverage data for impactful solutions! If anyone has recommendations for resources, or opportunities for internships or collaborations in the Data Science field, feel free to reach out—I’d love to connect and learn more! #DataScience #MachineLearning #Python #DataDriven #SQL #LearningJourney

Data Cleaning is one of the most important steps in ensuring the quality of Data for further processing it. Whenever a Data Analyst or Data Scientist wants to extract insights from the data, he/she should make sure that the data is clean, accurate, and ready for the process, otherwise, the insights generated from the data can have bad impacts. I found this book for Data Cleaning which is a must-read resource for anyone working with data. It shows all the data cleaning techniques in the best way with detailed explanation, relevant examples, and scenarios. I highly recommend this book for anyone working with data. Make sure to read this book and leave your thoughts in the comments section below. ----------------------------------------------------------- We provide information, tutorials, projects, internships, and much more about Data Analytics, Data Engineering, and Data Science fields on the Awesome Data channel. If you are interested, you may check it out. Channel Link: https://lnkd.in/ddWXfa9N #Data #DataAnalytics #DataEngineering #DataScience #DataCleaning #DataWrangling #DataProcessing #KnowledgeSharing #MustReadResource

🚀 Exciting News! 🚀 I'm thrilled to share that I've just completed an exciting project on Iris Flower Classification as part of my data science internship at Cipher Text! 🌸✨ In this project, I delved into the world of machine learning to classify different species of Iris flowers based on their measurements. From data exploration and preprocessing to model training and evaluation, it was a fantastic journey filled with learning and growth. 🌟 Key Highlights: 1. **Data Exploration and Visualization:** Understanding the intricate patterns in the data. 2. **Model Training and Cross-Validation:** Ensuring robust and reliable performance with a consistent cross-validation score of 93%. 3. **Hyperparameter Tuning:** Refining the model for optimal accuracy. I'm incredibly grateful for this opportunity and excited to continue honing my data science skills. 💡📊 GitHub link:- https://lnkd.in/gAHF2B8q I'm now looking for new opportunities to apply my skills and contribute to innovative projects in the field of data science and machine learning. If you have any openings or know of any opportunities, I'd love to connect! #DataScience #MachineLearning #IrisClassification #CareerGrowth #LearningJourney #AI #Tech #DataAnalysis #JobSeeker #CareerOpportunities #DataScienceIntern #Python #ModelEvaluation #LinkedInFamily