Mistakes 1) False expectations 2) Not following single roadmap 3) Lack of consistency 4)ignoring pillars of data science -python, sql and statistics 5)ignoring pillars of data science-Data Preprocessing, feature engineering ,exploratory data analysis 6) Not working on real-world datasets 7) wrong order of study(ML algorithms) 8) Not focusing on deployment 9) not starting interview preparation on day 1 10) not having mentor or study group
My mistake is to aim for perfection instead of completion.. learning the same thing in multiple ways which drains so much of time ..Research thodi kr rhe hain itna time bithane ke liye... Learning --Implementation---Learning--Growing .. cycle should be like this. And my other mistake is to ignore deployment of models
Mistake done by me while learning DS/ML/Python: Memorizing syntax - I was thinking I should write code without using google. Even in interview no one expects correct syntax from you, all they expect from u is how much you know concept. Though you must know basic syntax to clear coding round.
1. Revising python libraries again and again. It is a high possibility that you may forget the numpy pandas operations during execution. So you just need to take overview of code from internet and eventually you will start remembering them after 8-10 datasets. 2. Consistency - For this spiral method works which sir suggested i.e first take overview of topic and then do the topic again (Its like ek ek karke dhaage kholna) 3. No friends to study and never tried to talk with random. Extra: 4. Mental Health - Jabtak dimmag shaant nahi rahega , business wala dimaag nahi chalega aur fir data science mein maza bhi nahi aega.
1. Set fair time period to learn 2. Stick to one Roadmap 3. Consistency 4. Masters the pillars of data science (Python, SQL, Statistics & Maths) 5. Master -> Data Preprocessing, Feature Engineering, Exploratory Data Analysis 6. Try to work on Real Life Datasets 7. Give much time learning important ML algorithms 8. Deployment and management of Model 9. Prepare for interview simultaneously after learning anything 10. Motivation by mentor/study groups
1. Changed my roadmap quite a few times, which slowed my learning drastically. I think I studied same Pandas, Numpy, data viz libraries more than 2-3 times, but studied the same thing just for this mistake. 2. Inconsistency. I learnt, I stopped, and I forgot. And again the same circle!
I have done all these mistakes and was demotivated. I will start again after watching this video. I purchased your DSMP 2.0 program. I found a good teacher now but very late.Thank you for being so honest in your teachings and making ML concepts easier for us.
Mistakes in my DS journey 1. Focussing on implementation rather than in-depth knowldege. 2.Not getting into depth of things/ Having a superficial approach. 3. Thinking I understood it without actually understanding
The video was like a mirror for me . I realised I was doing the same mistakes, but still in my learning phase so I can rectify it. Thank you so much for sharing
I was learning ML for about a year (to be honest I was frustrated)and I saw this video, I am committing 6 out of these 10 mistakes. Thanks to him for letting me know what I was missing. In the last part where he mentions that one should have a mentor or a study group, I totally agree with that and that someone who wants to team up is welcomed.
All most all mistakes i have experienced from from same bhai.. and started over coming from them... any way thanks for sharing without any hesitation.... 👍
Me bhi yhi mistake kr rha hun 6 months me data science khatm...aapka roadmap sahi he ....consistent ni hona ek ar galti ...python ,sql ,statistics strong krna ye sahi baat he ...data clean krne pe aaj se focus rahega maximum....real world data set and pe abhi tak me try ni kiya ........interview preparation wali baat sabse important .........thanks for this suggestion
Sir i have followed all your course and for me you are best teacher regarding data science. I want you to create a playlist on model deployment and integration into website, android app and desktop application.
My mistake was that I was Inconsistent due to which I took gap after learning something. In my view consistency is very important in everything. No matter whatever you are learning.
Sabse badi galti ki kisi bhi institute ko bina sonche samjhe ya research kiye Bina join kar lena. Human nature hota hai ki first impression me agr koi chiz acchi lagi to hum usey hi consider krte hai aur isi cheez ka sales person advantage utha te hai. Before enrolling for any course try to ensure ki unka product kesa hai fomo me aakey join na kro. Aur Mentor ko khojne ki zrurat nahi hai wo yaha maujood hai sab Eklavya ban jao ab....
I think you have covered all common mistakes that anyone can do or have done in past. Apart from this, I think one can also be distracted by some other courses just by seeing their salary and scope or may lose hope by seeing any negative feedback or review about data science. So, if you have decided to become a data scientist then remain stick to the course until you got a start in this field
We r very lucky to have a mentor like u sir. Very greatful to u n ur channel. Thanku so much. I did same mistakes u told. Still learning. Now that ur channel is there , i stay motivated.
It's been almost 3 months i have started learning n practicing data science stuff trust me doing simple exploratory analysis on real world data is very difficult compare to learning ml dl models n maths
I mainly face problem in understanding deployment of models since I am from non CS background. I have a fair grasp and understanding of algos and statistics since I am a statistics student. Second thing is writing complex sql queries. I really face a hard time dealing with them.
I am master student in AI and all these things in my cirruculam 1. mistake I have not done learn theory that spoil time to learn practical and practice again so try both things parellel....theory and its practice
Guys I will recommend you for this course: Core Python (Hindi): ruclips.net/p/PLbGui_ZYuhigZkqrHbI_ZkPBrIr5Rsd5L Advance Python (Hindi): ruclips.net/p/PLbGui_ZYuhijd1hUF2VWiKt8FHNBa7kGb
12:05 #mistake no. 7 (wrong order of studying ML Algorithms) what did you said -> SBF(Selection By Filtering) OR SVM (Support Vector Machine).....Please Reply
Correctly said Bhai, inconsistent, less practice are my mistakes. Now i need to work on because I am from Non-tech background. While watching videos it looks like a cakewalk but in real it's not!!
3-Pillars Python, SQL , Maths(Stats, Linear Algebra, Probability) TOP 10 Machine Learning Agorithms Linear regression Logistic regression Decision tree SVM algorithm Naive Bayes algorithm KNN algorithm K-means Random forest algorithm Dimensionality reduction algorithms Gradient boosting algorithm and AdaBoosting algorithm Comment if Order is right, As I have just copied it from google.
1 KNN 2 naive bayes 3 linear regression 4 logistic regression 5 linear SVM 6 dual form of SVM 7 gradient descent 8 decision tree 9 random forest 10 GBDT 11 ada boost 12 Xgboost 13 PCA 14 t sne
I am an Aeronautical Engineer who wants to be in Data Science and i am learning all the skills needed by Data Analyst just to get a job and get going in the data field is this the right approach.
The biggest mistake I have done so far is that I became a perfectionist. In my opinion, you should find how much knowledge is important to just start and Practice, Practice, Practice. So that while practicing you will automatically start googling thing and learn.
I focused on only ml and I judge core python that was my mistake.... focused on only libraries which are like pandas ,numpy..etc In this field python is also more important....
Great video....I just started learning Data Science.....This video will really help me not make these mistakes. If anybody is also like me who have just started can connect to me to form a study group.
Can you take a survey on the same topic and display results where most people make mistakes because what you said is true to core also if you post on website it helps learner to have a glance plus we get evaluation were majority goes wrong 😅
Hi sir, i am new to your channel from machine learning roadmap video So now, i have to follow your this video and your ML and DL course of 100 days or i have to follow roadmap resources? Which one ?
1-> Not eating from one plate jumping here and there and last getting sleep without eating required food. 2-> Not having an proper mentor and also not having an partner of study. 3-> Not following a particular roadmap. 4-> Having so many resources to learn but don't know how to consume the efficient one with immediate effect. yet many others are there
Sir pls make a video on k fold cross validation Sir maine abhut saara video dekha par usme acche se explain nahi Kiya gaya hai Aap ek video banao aur statistics par bhi video banao Apne playlist me dusre ka video daala hai Sir it's very important for me I am watching only your video , getting understand with your video only Humble request from honest student to best teacher
This is definitely a helpful video. A mistake that I think I made was rushing too quickly into coding and not focussing more on basic stuff like MS Excel and SQL. Edit: Trying to land my first data role ever.
Array, string and Linked list ruclips.net/video/USxab2QN3hA/видео.html watch this video, you will get very useful advice, and then stop searching for this question, because Every one will say you have to like Software Engg aspirants easy and medium level leetcode and which is relevant for MAANG
Mistakes
1) False expectations
2) Not following single roadmap
3) Lack of consistency
4)ignoring pillars of data science -python, sql and statistics
5)ignoring pillars of data science-Data Preprocessing, feature engineering ,exploratory data analysis
6) Not working on real-world datasets
7) wrong order of study(ML algorithms)
8) Not focusing on deployment
9) not starting interview preparation on day 1
10) not having mentor or study group
My mistake is to aim for perfection instead of completion.. learning the same thing in multiple ways which drains so much of time ..Research thodi kr rhe hain itna time bithane ke liye... Learning --Implementation---Learning--Growing .. cycle should be like this. And my other mistake is to ignore deployment of models
Mistake done by me while learning DS/ML/Python:
Memorizing syntax - I was thinking I should write code without using google. Even in interview no one expects correct syntax from you, all they expect from u is how much you know concept. Though you must know basic syntax to clear coding round.
Thanks!
I haven't aced any interviews yet but aced all these mistakes Thank you for bringing these small(but big) mistakes into light.
1. Revising python libraries again and again. It is a high possibility that you may forget the numpy pandas operations during execution. So you just need to take overview of code from internet and eventually you will start remembering them after 8-10 datasets.
2. Consistency - For this spiral method works which sir suggested i.e first take overview of topic and then do the topic again (Its like ek ek karke dhaage kholna)
3. No friends to study and never tried to talk with random.
Extra:
4. Mental Health - Jabtak dimmag shaant nahi rahega , business wala dimaag nahi chalega aur fir data science mein maza bhi nahi aega.
totally agree , i spend 1 month ,and each of its day in frustration ,as i wanted to cover so many topics in one day.
could you be my mentor plz
Love you bhai ❤️
1. Set fair time period to learn
2. Stick to one Roadmap
3. Consistency
4. Masters the pillars of data science (Python, SQL, Statistics & Maths)
5. Master -> Data Preprocessing, Feature Engineering, Exploratory Data Analysis
6. Try to work on Real Life Datasets
7. Give much time learning important ML algorithms
8. Deployment and management of Model
9. Prepare for interview simultaneously after learning anything
10. Motivation by mentor/study groups
I'm following your machine learning roadmap from start to end. And deep learning is still going on. Thank you sir ❤
1. Changed my roadmap quite a few times, which slowed my learning drastically. I think I studied same Pandas, Numpy, data viz libraries more than 2-3 times, but studied the same thing just for this mistake.
2. Inconsistency. I learnt, I stopped, and I forgot. And again the same circle!
I have done all these mistakes and was demotivated. I will start again after watching this video. I purchased your DSMP 2.0 program. I found a good teacher now but very late.Thank you for being so honest in your teachings and making ML concepts easier for us.
hello bro whats up
kaisi chal rhi hai prep
Mistakes in my DS journey 1. Focussing on implementation rather than in-depth knowldege. 2.Not getting into depth of things/ Having a superficial approach. 3. Thinking I understood it without actually understanding
Great to know about you were a software developer !
It gave a quite motivation 😊
The video was like a mirror for me .
I realised I was doing the same mistakes, but still in my learning phase so I can rectify it.
Thank you so much for sharing
revisiting after 8 months
did the same mistakes again
but i am here again to recalibrate and take up on the action 01/01/25
I was learning ML for about a year (to be honest I was frustrated)and I saw this video, I am committing 6 out of these 10 mistakes. Thanks to him for letting me know what I was missing. In the last part where he mentions that one should have a mentor or a study group, I totally agree with that and that someone who wants to team up is welcomed.
I'm new to ml ,will u team up?
@@mysterysoul1936 sure we can
@@vedantbhenia9085 where can we start and communicate?
I too have the same story as you. I too am learning for over a year with lot of inconsistency.
I want to team up if its fine with you.
I also want to be in team,
Please add me too
All most all mistakes i have experienced from from same bhai.. and started over coming from them... any way thanks for sharing without any hesitation.... 👍
Me bhi yhi mistake kr rha hun 6 months me data science khatm...aapka roadmap sahi he ....consistent ni hona ek ar galti ...python ,sql ,statistics strong krna ye sahi baat he ...data clean krne pe aaj se focus rahega maximum....real world data set and pe abhi tak me try ni kiya ........interview preparation wali baat sabse important .........thanks for this suggestion
Sir i have followed all your course and for me you are best teacher regarding data science. I want you to create a playlist on model deployment and integration into website, android app and desktop application.
Now i am realising that I am doing same kind of mistakes.
Thank you so much.
My mistake was that I was Inconsistent due to which I took gap after learning something. In my view consistency is very important in everything. No matter whatever you are learning.
ye 10 points bahut zyada kaam ane wale hain...bahut zyada...shukriya nitish bhai ❤💯
Sabse badi galti ki kisi bhi institute ko bina sonche samjhe ya research kiye Bina join kar lena. Human nature hota hai ki first impression me agr koi chiz acchi lagi to hum usey hi consider krte hai aur isi cheez ka sales person advantage utha te hai. Before enrolling for any course try to ensure ki unka product kesa hai fomo me aakey join na kro. Aur Mentor ko khojne ki zrurat nahi hai wo yaha maujood hai sab Eklavya ban jao ab....
Thanks
I will be following your advice religiously from now on bro, thank you sharing these invaluable knowledge and tips
Hi bro are you getting started in data science we can connect on linked on
Your content is so valuable.....you must get millions of viewers
One day you will be
Thanks
I think you have covered all common mistakes that anyone can do or have done in past. Apart from this, I think one can also be distracted by some other courses just by seeing their salary and scope or may lose hope by seeing any negative feedback or review about data science. So, if you have decided to become a data scientist then remain stick to the course until you got a start in this field
Thank you sir, for the roadmap. Your videos are really good, to be frank it is perfect for people like us who are from non-technical background.
We r very lucky to have a mentor like u sir. Very greatful to u n ur channel. Thanku so much. I did same mistakes u told. Still learning. Now that ur channel is there , i stay motivated.
I am doing all these mistakes but thanks for this video now i know what i need to know or focus on
It's been almost 3 months i have started learning n practicing data science stuff trust me doing simple exploratory analysis on real world data is very difficult compare to learning ml dl models n maths
the same situation is going with me, thanks for guide.
I mainly face problem in understanding deployment of models since I am from non CS background.
I have a fair grasp and understanding of algos and statistics since I am a statistics student.
Second thing is writing complex sql queries. I really face a hard time dealing with them.
Loved to see you ❤️ awesome job brother
Bhaiya thanks, mentor nahi mila aap kai jaisa.
I am master student in AI and all these things in my cirruculam 1. mistake I have not done learn theory that spoil time to learn practical and practice again so try both things parellel....theory and its practice
Thanks for sharing this useful knowledge
I am following your roadmap , Thank you so much
That's some extremely good advice. Thank a lot for this.
Guys I will recommend you for this course:
Core Python (Hindi): ruclips.net/p/PLbGui_ZYuhigZkqrHbI_ZkPBrIr5Rsd5L
Advance Python (Hindi): ruclips.net/p/PLbGui_ZYuhijd1hUF2VWiKt8FHNBa7kGb
12:05 #mistake no. 7 (wrong order of studying ML Algorithms) what did you said -> SBF(Selection By Filtering) OR SVM (Support Vector Machine).....Please Reply
He said SVM
Please make one video on actual day to day work off datascientist or in other word what is the actual profile in company
Correctly said Bhai, inconsistent, less practice are my mistakes. Now i need to work on because I am from Non-tech background.
While watching videos it looks like a cakewalk but in real it's not!!
3-Pillars Python, SQL , Maths(Stats, Linear Algebra, Probability)
TOP 10 Machine Learning Agorithms
Linear regression
Logistic regression
Decision tree
SVM algorithm
Naive Bayes algorithm
KNN algorithm
K-means
Random forest algorithm
Dimensionality reduction algorithms
Gradient boosting algorithm and AdaBoosting algorithm
Comment if Order is right, As I have just copied it from google.
1 KNN 2 naive bayes 3 linear regression 4 logistic regression 5 linear SVM 6 dual form of SVM 7 gradient descent 8 decision tree 9 random forest 10 GBDT 11 ada boost 12 Xgboost 13 PCA 14 t sne
you miss the main one merge the skills with different business domain
Python maa expert bnana k lia konsa platform best ha. Although k aap k bee ha. Aap apna ilawa kis ko suggest kroo ga.
I am an Aeronautical Engineer who wants to be in Data Science and i am learning all the skills needed by Data Analyst just to get a job and get going in the data field is this the right approach.
Why are you come to data science filed?
@@atharvkumar9740 Because I am Interested
Thank you sir for your valuable lessons
Thanks for these priceless tips Legend Nitish Sir
This channel is underrated
The biggest mistake I have done so far is that I became a perfectionist. In my opinion, you should find how much knowledge is important to just start and Practice, Practice, Practice. So that while practicing you will automatically start googling thing and learn.
I focused on only ml and I judge core python that was my mistake.... focused on only libraries which are like pandas ,numpy..etc In this field python is also more important....
could you be my mentor plz or suggest any
You have covered the syllabus along with mistakes. Syllabus is huge
Nice advice bro...you saved tones of time
Thank yoy so much this will be extremely helpful for me.
Please made a vedio on open source contribution in field of data science
Can you please make a playlist of end to end project using real time dataset .
How much python is needed for data science or data analysis
Suppose I completed a topic eg mangoDB or stats. So where can I find projects related to the topics which I have completed?
Great video....I just started learning Data Science.....This video will really help me not make these mistakes. If anybody is also like me who have just started can connect to me to form a study group.
how's your journey going??
Disquard ka link hai kya
Bahut achchha video hai guys
Bhai source b bta do kaise pdhna hai kahn se ??
Though i have already done most mistakes but I'll try to improvise them from now onwards.
Biggest mistake not having mentor like you yet
Yes you are right.
I have done all this mistake, join creating any study group should be first thing I have to do.
Feature engineering kya hota he?
Discord group kaise join kare
Sir I m not getting ur discord community plzz help
Nice advice..... it helps a lot..
Can you take a survey on the same topic and display results where most people make mistakes because what you said is true to core also if you post on website it helps learner to have a glance plus we get evaluation were majority goes wrong 😅
Thankyou so much 😊✨🌼
Hi sir, i am new to your channel from machine learning roadmap video
So now, i have to follow your this video and your ML and DL course of 100 days or i have to follow roadmap resources?
Which one ?
Roadmap
What is discort community?How can I join?
very informative video. 🙏🙏🙏🙏
Is Data science field bright in 2023?
Future scopes comparing others tech fields?
I have statistics background my mistake is, do not practice regularly of coding.
sir data analytics k liye bataiye kaise start kare
1-> Not eating from one plate jumping here and there and last getting sleep without eating required food.
2-> Not having an proper mentor and also not having an partner of study.
3-> Not following a particular roadmap.
4-> Having so many resources to learn but don't know how to consume the efficient one with immediate effect.
yet many others are there
How much python should I master...like I have done the basics till object oriented programming
Amazing ❤
sir please make a full data science roadmap for us🙏🙏🙏🙏🙏🙏🙏
Sir final year wale data science and DSA ko kese manage kare study k lie
Thank you sir ....
plz sir time series forecasting p video bnao.
Sir, ek deep learning roadmap
Great mentor for me
I have ignored deployment. Need to focus on it.
Sir i also started learning ml algo initially and was not knowing python sql. I face difficulties daily
2nd one happened with me as well...
Sir pls make a video on k fold cross validation
Sir maine abhut saara video dekha par usme acche se explain nahi Kiya gaya hai
Aap ek video banao aur statistics par bhi video banao
Apne playlist me dusre ka video daala hai
Sir it's very important for me I am watching only your video , getting understand with your video only
Humble request from honest student to best teacher
Interview clear karne ke liye kitna syllabus padhna chahiye and kitna time lagega ?
I didn't work on end to end project.
This is definitely a helpful video. A mistake that I think I made was rushing too quickly into coding and not focussing more on basic stuff like MS Excel and SQL.
Edit: Trying to land my first data role ever.
U saved my life thankyou ❤️
How to join discord group?
Thankyou sir, I am following your Roadmap. Sir, can you please update the roadmap since you said you will update some more things.
Sir where did you learn data science, can u tell that ??
Thank you so much ❤
Thank you so much sir
Sir mujhe yeh ni smj aata h ki mai python kse seekhu mtlb kaha se start Karu kya kya sikhku sirf data science ke liye
Taking coding ninja python with dsa course acche se ho jaega python
where is your discord group sir?
Is data structures alogo is imp for data science?
Same question
I think it's not important for data science...but if u want placement then u surely have to learn it
It’s important bro do till leetcode medium questions, and cover till Bst, hard questions and graphs dp’s questions are not much asked
Array, string and Linked list ruclips.net/video/USxab2QN3hA/видео.html watch this video, you will get very useful advice, and then stop searching for this question, because Every one will say you have to like Software Engg aspirants easy and medium level leetcode and which is relevant for MAANG
Sir is 100days of machine learning playlist enough to crack machine learning interviews??