5 LPA to 50+ LPA in 2 YEARS 🔥! Ultimate DATA SCIENTIST @ Microsoft 🔥 FRESHER Cracked SENIOR Role ❤️



🔴 Register for CodeKaze test, 30 Lakh Prize – https://bit.ly/3sL1LG5

🔅 Follow Me On Instagram – https://www.instagram.com/_shashank_219/

📱 𝗖𝗼𝗻𝗻𝗲𝗰𝘁 𝗪𝗶𝘁𝗵 Prashant :
🔴 LinkedIn – https://www.linkedin.com/in/prashantg445/

𝗝𝗼𝗶𝗻 𝗺𝗲 𝗼𝗻 𝗦𝗼𝗰𝗶𝗮𝗹 𝗠𝗲𝗱𝗶𝗮:🔥
🔅Shashank LinkedIn – https://www.linkedin.com/in/shashank219/
🔅Shashank Instagram – https://www.instagram.com/_shashank_219/
🔅Telegram Group – LearningBridge
⭕Discord Server – https://discord.io/shashankELB
🔴Join for 1×1 Mentorship, Mock Interviews, Career Guidance, Resume Building, Interview roadmap and resources to crack tech, BigData/Data Engineering tutorials from scratch :
https://www.youtube.com/channel/UCBGcs9XTL5U34oaSn_AsHqw/join

𝗗𝗶𝘀𝗰𝘂𝘀𝘀𝗲𝗱 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻𝘀:

✅ 0:00 — Inspiring Podcast Precap
✅ 1:13 — CodeKaze Test for 30 Lakh Prize
✅ 2:01 — Prashant’s Introduction
✅ 3:05 — Data Science Journey From College
✅ 6:16 — Microsoft Interview Experience For Data Science Role
✅ 10:27 — Data Science Guide For Freshers
✅ 14:34 — Best resources to follow for Data Science
✅ 16:42 — is Coding important for Data Science Role?
✅ 19:19 — How to get more interview calls?
✅ 20:43 — Myths about Data Scientists
✅ 23:13 — Data Scientists Salary

#microsoft #datascientist #InterviewExperience

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30 thoughts on “5 LPA to 50+ LPA in 2 YEARS 🔥! Ultimate DATA SCIENTIST @ Microsoft 🔥 FRESHER Cracked SENIOR Role ❤️”
  1. Curating all the resources that I mentioned in the video:

    Prerequisites:
    Basic level Math (mainly probability, linear algebra, differential calculus, statistics)
    Basic level Python (can learn from anywhere & practice few coding problems on it)

    Tools to play with data:
    (Kaggle will be really helpful here not just in terms of datasets, but it's EDA discussions)
    SQL
    Numpy
    Matplotlib
    Pandas (for tabular data)
    Opencv (for image data)
    Satosa (for understanding image kernels)
    NLTK (for text data)

    ML:
    Statquest YT channel (for understanding algorithms)
    Scikit-learn package (for all essential preprocessing and ML implementations with a nice doc)

    Deep Learning:
    Deep learning specialization (5 courses) by Andrew NG
    TF playground (for understanding basic working of neural networks)
    Stanford CS 231 course by Andrej Karpathy (I did it at that time, maybe some better courses are available now)
    Stanford 224 (NLP)

    I generally rely on blogs for everything. You may follow blogs like:
    Jay Alammar
    Colah (best for lstm)
    Sebastian ruder (word embeddings and gradient descent optimizers)
    MLWhiz (ML fundamentals)

    YT channels for Interview practice:
    Krish Naik
    Data Science Jay
    Nick Singh (on linkedin)

    For finding best available model in any field: Paperswithcode

    I can go on and on but this list will never end. And once you become familiar enough, you don't need any further suggestions. Keep hustling !!

  2. yes I am a fresher data scientist and would love if you bring different data scientist from different companies to share their experience

  3. Thanks a lot, Brother!
    This video helped me a lot and as I was suffering from a lot of confusion in this field, these kinds of videos are actually lifesavers…..

  4. Sir i am from Mechanical 2020 passout
    Wanted to switch career into data science.
    Please suggest me is it right decision to pursue this as career. And how can I master this if possible for me….

  5. I m pursuing BBA so can I go for data science despite from non IT/Maths/Stats background.
    Will I be able to get such packages?

  6. Is there anybody who is from non IT, non maths/stats background and still got a handsome package?

  7. Please make a video with a cloud engineer it will help for those student who is interested in cloud.

  8. Deep learning (Neural Network )is just another algorithm its not like if you don't know Linear regression SVM, decision trees you cant understand Neural network

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