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Scaler Data Science
& Machine Learning Program
Unlock the power of data with Scaler's Data Science course, mastering crucial skills for success in the field, all backed by secure placement support.
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1:1 mentorship
Industry projects
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Free Guidance On DevOps & Software Development
By Anshuman Singh
Co-Founder at Scaler Academy
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Scheduling for :
11th Sep 2024 | 07:00 PM - 09:00 PM
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Attend a Free Class to Experience The Scaler Data Science Program
By Srikant Varma Chekuri
Instructor at Scaler Data Science
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Scheduling for :
12th Sep 2024 | 07:00 PM - 09:00 PM
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Free Guidance On DevOps & Software Development
By Anshuman Singh
Co-Founder at Scaler Academy
11th Sep 2024
07:00 PM - 09:00 PM
Free Guidance On DevOps & Software Development
By Anshuman Singh
Co-Founder at Scaler Academy
14th Sep 2024
12:00 PM - 02:00 PM
Attend a Free Class to Experience The Scaler Data Science Program
By Srikant Varma Chekuri
Instructor at Scaler Data Science
12th Sep 2024
07:00 PM - 09:00 PM
Attend a Free Class to Experience The Scaler Data Science Program
By Srikant Varma Chekuri
Instructor at Scaler Data Science
14th Sep 2024
12:00 PM - 02:00 PM
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Next Batch starts in SEPTEMBER
Find our Alumnis at -
Why Scaler Data Science & Machine Learning Program?
Scaler’s Data Science course is a program curated to help you kick-start your career in Data Science & Machine Learning. We’ll make you industry-ready through a rigorous curriculum taught by industry veterans who’ll mentor you as you headway toward growth.
Monthly 1:1 mentorship by industry experts to provide personalized guidance and support.
Learn from industry-leading experts who have built FB messenger, Uber, etc.
50+ Hands-on projects and real-world case studies enrich your learning experience.
Get Expert career guidance to help you navigate your path in data science.
Master essential tools and languages used in data science and machine learning.
Join a thriving community of learners and alumni for networking and support.
1:1 Mentorship
Monthly 1:1 mentorship by industry experts to provide personalized guidance and support.
Top Instructors
Learn from industry-leading experts who have built FB messenger, Uber, etc.
Projects and Case Studies
50+ Hands-on projects and real-world case studies enrich your learning experience.
Career Counselling
Get Expert career guidance to help you navigate your path in data science.
Tools and Languages
Master essential tools and languages used in data science and machine learning.
Learners & Alumni Network
Join a thriving community of learners and alumni for networking and support.
1.
What kind of projects are included as part of this Data Science course?
Projects from top companies to make you a real Data Scientist or ML Engineer.
Gain practical experience through real data sets and projects developed in collaboration with leading companies.
View more projects >
All Projects
Online Security
Decide which transactions should be blocked to keep users safe.
Network Optimization
Optimize network speed by minimizing junk traffic and spammy bots.
Improve Product Design
Make the checkout experience flawless to boost sales.
Improve User Experience
Make the games and app more engaging to boost daily usage
Predict ETA
Predict when would medicine arrive at customer's addresses.
Recommendation Engine
Show personalized recommendations to improve user experience.
Online Security
Decide which transactions should be blocked to keep users safe.
Network Optimization
Optimize network speed by minimizing junk traffic and spammy bots.
Improve Product Design
Make the checkout experience flawless to boost sales.
Improve User Experience
Make the games and app more engaging to boost daily usage
Predict ETA
Predict when would medicine arrive at customer's addresses.
Recommendation Engine
Show personalized recommendations to improve user experience.
Online Security
Decide which transactions should be blocked to keep users safe.
Network Optimization
Optimize network speed by minimizing junk traffic and spammy bots.
Improve Product Design
Make the checkout experience flawless to boost sales.
Improve User Experience
Make the games and app more engaging to boost daily usage
Predict ETA
Predict when would medicine arrive at customer's addresses.
Recommendation Engine
Show personalized recommendations to improve user experience.
Sahil Chelaramani
Ex
read more
Hitesh Hinduja
Ex
read more
Aakash Agarwal
Ex
read more
Deepak Gupta
Ex
read more
Sanjeev Singh
Ex
read more
Naga Budigam
Ex
read more
Sahil Chelaramani
Ex
read less
- Data Scientist, Microsoft
- Senior Manager - Artificial Intelligence
- He has worked on Bing Search and Azure Global Development teams. He has experience in building large Deep Learning projects, and Data Science solutions.
Hitesh Hinduja
Ex
read less
- Ola Electric
- Senior Manager - Artificial Intelligence
- Leading Ola Electric Data Science, Smart Mobility at OLA with a team of 20 people Developing products with end to end ML pipelines
Aakash Agarwal
Ex
read less
- Mastercard
- Senior Member of a corporate research (Data Scientists) team who develops state of the art NLP products which improves business at scale.
Deepak Gupta
Ex
read less
- Bosch Center for Artificial Intelligence (BCAI)
- Senior Data Scientist
- Senior Member of a corporate research (Data Scientists) team who develops state of the art NLP products which improves business at scale.
Sanjeev Singh
Ex
read less
- BharatPe
- Head of Data Platform & Engineering
- Heading BharatPe Data Platform and Engineering, Building End to End Data Pipeline , Data warehouse and Reporting solution. Providing Data Solution & Insights for Nex Gen Fintech and Banking in BharatPe.
Naga Budigam
Ex
read less
- TVS Motor Company
- Lead Data Scientist
- Understanding business problems , translate them into AI/ML problems with a team of 11 Data Scientist and Build MVPs and conduct the DOEs to quantify the incremental benefit obtained through the AI/ML solution/product.
2.
What if I get stuck or need guidance?
Get 1:1 Mentorship from Expert Data Scientists and ML Engineers!
Speak 1:1 with your mentor to get all your data science related queries and doubts answered, help you define your career paths, conduct mock interviews, and give you detailed feedback.
View all
Your Mentors
Sahil Chelaramani
Ex
read more
Hitesh Hinduja
Ex
read more
Aakash Agarwal
Ex
read more
Deepak Gupta
Ex
read more
Sanjeev Singh
Ex
read more
Naga Budigam
Ex
read more
3.
Will I get Placement Assistance?
Create real-world impact with your new skillset!
Companies wish to hire data scientists and ML engineers who are not just certified and skilled but also have a deep understanding of business. We at Scaler help you achieve the best skillset and help you get job opportunities from top companies.
Resume Making
Help with Referrals
Mock Interview
Career Counselling
4.
Which Data Science tools would I learn?
“Git” better at predicting & manipulating data with an array of tools!
Learn 45+ Data Science tools, including Git, TensorFlow, PySpark, PyTorch, and Kafka.
Meet the people who made it to the top companies
Ayan Sengupta
System Dev Engineer
DSML Nov21 Intermediate
Trianz
Courses like DSA and DSML with Scaler stood out to me because they'd provide you with every resource possible to enhance your learning. The only thing that you'd be required to dedicate all around the course would be commitment!
Tai Rakesh Kumar
Data Engineer
DSML Feb22 Advanced
TCS
Coming from a less privileged background, the course has done wonders for me. Would recommend the Scaler program, especially DSML to engineers wanting to enter and grow in the sector of AI & ML
Arun M V
Applied scientist
DSML Nov21 Intermediate
Qualcomm
Choosing the scaler course was the best decision I have made for my career growth.Throughout my journey with scaler, it was more like a fun way to learn and develop skills. With every session, I used to be more and more curious. It never felt like a chore to attend the classes. Even after having a tiring day, I always looked forward to learning and enjoying the scaler sessions at night.
Abhishek singh
FullStack Engineer
DSML Nov21 Beginner
Sun Life
I took assistance from Scaler, and little did I know when I enrolled in the course that not only will I thoroughly enjoy my time there, but secure my dream placement as well :)
Harsh Patel
Data Scientist
DSML Mar22 Beginner
ABB
While I don't come from a tech-savvy city like Bangalore, with Scaler's help I could dream of making a great career in Data Science
Ayan Sengupta
System Dev Engineer
DSML Nov21 Intermediate
Trianz
Courses like DSA and DSML with Scaler stood out to me because they'd provide you with every resource possible to enhance your learning. The only thing that you'd be required to dedicate all around the course would be commitment!
Tai Rakesh Kumar
Data Engineer
DSML Feb22 Advanced
TCS
Coming from a less privileged background, the course has done wonders for me. Would recommend the Scaler program, especially DSML to engineers wanting to enter and grow in the sector of AI & ML
Arun M V
Applied scientist
DSML Nov21 Intermediate
Qualcomm
Choosing the scaler course was the best decision I have made for my career growth.Throughout my journey with scaler, it was more like a fun way to learn and develop skills. With every session, I used to be more and more curious. It never felt like a chore to attend the classes. Even after having a tiring day, I always looked forward to learning and enjoying the scaler sessions at night.
All Alumni
Ayan Sengupta
System Dev Engineer
DSML Nov21 Intermediate
Trianz
Courses like DSA and DSML with Scaler stood out to me because they'd provide you with every resource possible to enhance your learning. The only thing that you'd be required to dedicate all around the course would be commitment!
Tai Rakesh Kumar
Data Engineer
DSML Feb22 Advanced
TCS
Coming from a less privileged background, the course has done wonders for me. Would recommend the Scaler program, especially DSML to engineers wanting to enter and grow in the sector of AI & ML
Arun M V
Applied scientist
DSML Nov21 Intermediate
Qualcomm
Choosing the scaler course was the best decision I have made for my career growth.Throughout my journey with scaler, it was more like a fun way to learn and develop skills. With every session, I used to be more and more curious. It never felt like a chore to attend the classes. Even after having a tiring day, I always looked forward to learning and enjoying the scaler sessions at night.
Abhishek singh
FullStack Engineer
DSML Nov21 Beginner
Sun Life
I took assistance from Scaler, and little did I know when I enrolled in the course that not only will I thoroughly enjoy my time there, but secure my dream placement as well :)
Harsh Patel
Data Scientist
DSML Mar22 Beginner
ABB
While I don't come from a tech-savvy city like Bangalore, with Scaler's help I could dream of making a great career in Data Science
Ayan Sengupta
System Dev Engineer
DSML Nov21 Intermediate
Trianz
Courses like DSA and DSML with Scaler stood out to me because they'd provide you with every resource possible to enhance your learning. The only thing that you'd be required to dedicate all around the course would be commitment!
Years of experience at the time of joining Scaler
4
College
Siksha 'O' Anusandhan University
Degree
B.Tech
Scaler Graduation Year
2021
Tai Rakesh Kumar
Data Engineer
DSML Feb22 Advanced
TCS
Coming from a less privileged background, the course has done wonders for me. Would recommend the Scaler program, especially DSML to engineers wanting to enter and grow in the sector of AI & ML
Years of experience at the time of joining Scaler
2
College
Gayatri Vidya Parishad College Of Engineering
Degree
B.Tech
Scaler Graduation Year
2022
Arun M V
Applied scientist
DSML Nov21 Intermediate
Qualcomm
Choosing the scaler course was the best decision I have made for my career growth.Throughout my journey with scaler, it was more like a fun way to learn and develop skills. With every session, I used to be more and more curious. It never felt like a chore to attend the classes. Even after having a tiring day, I always looked forward to learning and enjoying the scaler sessions at night.
Years of experience at the time of joining Scaler
1
College
Sri Jayachamarajendra College Of Engineering Mysore
Degree
B.Tech
Scaler Graduation Year
2021
Abhishek singh
FullStack Engineer
DSML Nov21 Beginner
Sun Life
I took assistance from Scaler, and little did I know when I enrolled in the course that not only will I thoroughly enjoy my time there, but secure my dream placement as well :)
Years of experience at the time of joining Scaler
2
College
VIT Chennai
Degree
B.Tech
Scaler Graduation Year
2021
Harsh Patel
Data Scientist
DSML Mar22 Beginner
ABB
While I don't come from a tech-savvy city like Bangalore, with Scaler's help I could dream of making a great career in Data Science
Years of experience at the time of joining Scaler
2
College
School Of Engineering And Applied Sciences Ahmedabad University
Degree
B.Tech
Scaler Graduation Year
2022
5.
Is Scaler’s Data science course’s curriculum aligned with the industry?
Up-to-date curriculum with the fast-evolving Data Science and ML field.
Beginner
15 Months
Intermediate
11 Months
Advanced
7 Months
Module - 1
Beginner Module
5 Months
Module - 2
Data Analysis and Visualization
4 Months
Module - 3
Foundations of Machine Learning and Deep Learning
3 Months
Module - 4
Specializations
3 Months
Module - 5
Machine Learning Ops
1 Month
Module - 6
Advanced Data Structures and Algorithms
4 Months
5 Months
Tableau + Excel
Basic Visual Analytics
More Charts and Graphs, Operations on Data and Calculations in Tableau
Advanced Visual Analytics and Level Of Detail (LOD) Expressions
Geographic Visualizations, Advanced Charts, and Worksheet and Workbook Formatting
Introduction to Excel and Formulas
Pivot Tables, Charts and Statistical functions
Google Spreadsheets
SQL
Intro to Databases & BigQuery Setup
Extracting data using SQL
Functions, Filtering and Subqueries
Joins
GROUP BY & Aggregation
Window Functions
Date and Time Functions & CTEs
Indexes and Partitioning
Python
Flowcharts, Data Types, Operators
Conditional Statements & Loops
Functions
Strings
In-built Data Structures - List, Tuple, Dictionary, Set, Matrix Algebra, Number Systems
Python Refresher
Basics of Time and Space Complexity
OOPS
Functional Programming
Exception Handling and Modules
4 Months
Python libraries
Numpy, Pandas
Matplotlib
Seaborn
Data Acquisition
Web API
Web Scraping
Beautifulsoup
Tweepy
Probability and Applied Statistics
Probability
Bayes Theorem
Distributions
Descriptive Statistics, outlier treatment
Confidence Interval
Central limit theorem
Hypothesis test, AB testing
ANOVA
Correlation
EDA, Feature Engineering, Missing value treatment
Experiment Design
Regex, NLTK, OpenCV
Product Analytics
Framework to address product sense questions
Diagnostics
Metrics, KPI
Product Design & Development
Guesstimates
Product Cases from Netflix, Stripe, Instagram
3 Months
You can move to the advanced track only after you clear the transition test
Math for Machine Learning
Classification
Hyperplane
Halfspaces
Calculus
Optimization
Gradient descent
Principal Component Analysis
Introduction to Neural Networks and Machine Learning
Introduction to Classical Machine Learning
Linear Regression
Polynomial, Bias-Variance, Regularisation
Cross Validation
Logistic Regression-2
Perceptron and Softmax Classification
Introduction to Clustering, k-Means
K-means ++, Hierarchical
3 Months each
You can pursue the Deep Learning specialisation after completing the Machine Learning specialisation or vice versa
Machine Learning
Machine Learning 1: Supervised
MLE, MAP, Confidence Interval
Classification Metrics
Imbalanced Data
Decision Trees
Bagging
Naive Bayes
SVM
Machine Learning 2: Unsupervised and Recommender systems
Intro to Clustering, k-Means
K-means ++, Hierarchical
GMM
Anomaly/Outlier/Novelty Detection
PCA, t-SNE
Recommender Systems
Time Series Analysis
And/Or
Deep Learning
Neural Networks
Perceptrons
Neural Networks
Hidden Layers
Tensorflow
Keras
Forward and Back Propagation
Multilayer Perceptrons (MLP)
Callbacks
Tensorboard
Optimization
Hyperparameter tuning
Computer vision
Convolutional Neural Nets
Data Augmentation
Transfer Learning
CNN
CNN hyperparameters tuning & BackPropagation
CNN Visualization
Popular CNN Architecture - Alex, VGG, ResNet, Inception, EfficientNet, MobileNet
Object Segmentation, Localisation, and Detection
Generative Models, GANs
Attention Models
Siamese Networks
Advanced CV
Natural Language Processing
Text Processing and Representation
Tokenization, Stemming, Lemmatization
Vector space modelling, Cosine Similarity, Euclidean Distance
POS tagging, Dependency parsing
Topic Modeling, Language Modeling
Embeddings
Recurrent Neural Nets
Information Extraction
LSTM
Attention
Named Entity Recognition
Transformers
HuggingFace
BERT
1 Month
Machine Learning Ops
Streamlit
Flask
Containerisation, Docker
Experiment Tracking
MLFlow
CI/CD
GitHub Actions
ML System Design
AWS Sagemaker, AWS Data Wrangler, AWS Pipeline
Apache Spark
Spark MLlib
4 Months
The recorded lectures of Advanced Programming will be shared along with Teaching Assistant support (no live sessions)
Advanced Data Structures and Algorithms
Linked Lists
Stacks & Queues
Trees
Tries & Heaps
Module - 1
Data Analysis and Visualization
4 Months
Module - 2
Foundations of Machine Learning and Deep Learning
3 Months
Module - 3
Specializations
3 Months
Module - 4
Machine Learning Ops
1 Month
Module - 5
Advanced Data Structures and Algorithms
4 Months
4 Months
Python libraries
Numpy, Pandas
Matplotlib
Seaborn
Data Acquisition
Web API
Web Scraping
Beautifulsoup
Tweepy
Probability and Applied Statistics
Probability
Bayes Theorem
Distributions
Descriptive Statistics, outlier treatment
Confidence Interval
Central limit theorem
Hypothesis test, AB testing
ANOVA
Correlation
EDA, Feature Engineering, Missing value treatment
Experiment Design
Regex, NLTK, OpenCV
Product Analytics
Framework to address product sense questions
Diagnostics
Metrics, KPI
Product Design & Development
Guesstimates
Product Cases from Netflix, Stripe, Instagram
3 Months
You can move to the advanced track only after you clear the transition test
Advanced Python
Python Refresher
Basics of Time and Space Complexity
OOPS
Functional Programming
Exception Handling and Modules
Math for Machine Learning
Classification
Hyperplane
Halfspaces
Calculus
Optimization
Gradient descent
Principal Component Analysis
Introduction to Neural Networks and Machine Learning
Introduction to Classical Machine Learning
Linear Regression
Polynomial, Bias-Variance, Regularisation
Cross Validation
Logistic Regression-2
Perceptron and Softmax Classification
Introduction to Clustering, k-Means
K-means ++, Hierarchical
3 Months each
You can pursue the Deep Learning specialisation after completing the Machine Learning specialisation or vice versa
Machine Learning
Machine Learning 1: Supervised
MLE, MAP, Confidence Interval
Classification Metrics
Imbalanced Data
Decision Trees
Bagging
Naive Bayes
SVM
Machine Learning 2: Unsupervised and Recommender systems
Intro to Clustering, k-Means
K-means ++, Hierarchical
GMM
Anomaly/Outlier/Novelty Detection
PCA, t-SNE
Recommender Systems
Time Series Analysis
And/Or
Deep Learning
Neural Networks
Perceptrons
Neural Networks
Hidden Layers
Tensorflow
Keras
Forward and Back Propagation
Multilayer Perceptrons (MLP)
Callbacks
Tensorboard
Optimization
Hyperparameter tuning
Computer vision
Convolutional Neural Nets
Data Augmentation
Transfer Learning
CNN
CNN hyperparameters tuning & BackPropagation
CNN Visualization
Popular CNN Architecture - Alex, VGG, ResNet, Inception, EfficientNet, MobileNet
Object Segmentation, Localisation, and Detection
Generative Models, GANs
Attention Models
Siamese Networks
Advanced CV
Natural Language Processing
Text Processing and Representation
Tokenization, Stemming, Lemmatization
Vector space modelling, Cosine Similarity, Euclidean Distance
POS tagging, Dependency parsing
Topic Modeling, Language Modeling
Embeddings
Recurrent Neural Nets
Information Extraction
LSTM
Attention
Named Entity Recognition
Transformers
HuggingFace
BERT
1 Month
Machine Learning Ops
Streamlit
Flask
Containerisation, Docker
Experiment Tracking
MLFlow
CI/CD
GitHub Actions
ML System Design
AWS Sagemaker, AWS Data Wrangler, AWS Pipeline
Apache Spark
Spark MLlib
4 Months
The recorded lectures of Advanced Programming will be shared along with Teaching Assistant support (no live sessions)
Advanced Data Structures and Algorithms
Linked Lists
Stacks & Queues
Trees
Tries & Heaps
Module - 1
Foundations of Machine Learning and Deep Learning
3 Months
Module - 2
Specializations
3 Months
Module - 3
Machine Learning Ops
1 Month
Module - 4
Advanced Data Structures and Algorithms
4 Months
3 Months
You can move to the advanced track only after you clear the transition test
Advanced Python
Python Refresher
Basics of Time and Space Complexity
OOPS
Functional Programming
Exception Handling and Modules
Math for Machine Learning
Classification
Hyperplane
Halfspaces
Calculus
Optimization
Gradient descent
Principal Component Analysis
Introduction to Neural Networks and Machine Learning
Introduction to Classical Machine Learning
Linear Regression
Polynomial, Bias-Variance, Regularisation
Cross Validation
Logistic Regression-2
Perceptron and Softmax Classification
Introduction to Clustering, k-Means
K-means ++, Hierarchical
3 Months each
You can pursue the Deep Learning specialisation after completing the Machine Learning specialisation or vice versa
Machine Learning
Machine Learning 1: Supervised
MLE, MAP, Confidence Interval
Classification Metrics
Imbalanced Data
Decision Trees
Bagging
Naive Bayes
SVM
Machine Learning 2: Unsupervised and Recommender systems
Intro to Clustering, k-Means
K-means ++, Hierarchical
GMM
Anomaly/Outlier/Novelty Detection
PCA, t-SNE
Recommender Systems
Time Series Analysis
And/Or
Deep Learning
Neural Networks
Perceptrons
Neural Networks
Hidden Layers
Tensorflow
Keras
Forward and Back Propagation
Multilayer Perceptrons (MLP)
Callbacks
Tensorboard
Optimization
Hyperparameter tuning
Computer vision
Convolutional Neural Nets
Data Augmentation
Transfer Learning
CNN
CNN hyperparameters tuning & BackPropagation
CNN Visualization
Popular CNN Architecture - Alex, VGG, ResNet, Inception, EfficientNet, MobileNet
Object Segmentation, Localisation, and Detection
Generative Models, GANs
Attention Models
Siamese Networks
Advanced CV
Natural Language Processing
Text Processing and Representation
Tokenization, Stemming, Lemmatization
Vector space modelling, Cosine Similarity, Euclidean Distance
POS tagging, Dependency parsing
Topic Modeling, Language Modeling
Embeddings
Recurrent Neural Nets
Information Extraction
LSTM
Attention
Named Entity Recognition
Transformers
HuggingFace
BERT
1 Month
Machine Learning Ops
Streamlit
Flask
Containerisation, Docker
Experiment Tracking
MLFlow
CI/CD
GitHub Actions
ML System Design
AWS Sagemaker, AWS Data Wrangler, AWS Pipeline
Apache Spark
Spark MLlib
4 Months
The recorded lectures of Advanced Programming will be shared along with Teaching Assistant support (no live sessions)
Advanced Data Structures and Algorithms
Linked Lists
Stacks & Queues
Trees
Tries & Heaps
5 Months
Tableau + Excel
Basic Visual Analytics
More Charts and Graphs, Operations on Data and Calculations in Tableau
Advanced Visual Analytics and Level Of Detail (LOD) Expressions
Geographic Visualizations, Advanced Charts, and Worksheet and Workbook Formatting
Introduction to Excel and Formulas
Pivot Tables, Charts and Statistical functions
Google Spreadsheets
SQL
Intro to Databases & BigQuery Setup
Extracting data using SQL
Functions, Filtering and Subqueries
Joins
GROUP BY & Aggregation
Window Functions
Date and Time Functions & CTEs
Indexes and Partitioning
Python
Flowcharts, Data Types, Operators
Conditional Statements & Loops
Functions
Strings
In-built Data Structures - List, Tuple, Dictionary, Set, Matrix Algebra, Number Systems
Python Refresher
Basics of Time and Space Complexity
OOPS
Functional Programming
Exception Handling and Modules
4 Months
Python libraries
Numpy, Pandas
Matplotlib
Seaborn
Data Acquisition
Web API
Web Scraping
Beautifulsoup
Tweepy
Probability and Applied Statistics
Probability
Bayes Theorem
Distributions
Descriptive Statistics, outlier treatment
Confidence Interval
Central limit theorem
Hypothesis test, AB testing
ANOVA
Correlation
EDA, Feature Engineering, Missing value treatment
Experiment Design
Regex, NLTK, OpenCV
Product Analytics
Framework to address product sense questions
Diagnostics
Metrics, KPI
Product Design & Development
Guesstimates
Product Cases from Netflix, Stripe, Instagram
3 Months
You can move to the advanced track only after you clear the transition test
Math for Machine Learning
Classification
Hyperplane
Halfspaces
Calculus
Optimization
Gradient descent
Principal Component Analysis
Introduction to Neural Networks and Machine Learning
Introduction to Classical Machine Learning
Linear Regression
Polynomial, Bias-Variance, Regularisation
Cross Validation
Logistic Regression-2
Perceptron and Softmax Classification
Introduction to Clustering, k-Means
K-means ++, Hierarchical
3 Months each
You can pursue the Deep Learning specialisation after completing the Machine Learning specialisation or vice versa
Machine Learning
Machine Learning 1: Supervised
MLE, MAP, Confidence Interval
Classification Metrics
Imbalanced Data
Decision Trees
Bagging
Naive Bayes
SVM
Machine Learning 2: Unsupervised and Recommender systems
Intro to Clustering, k-Means
K-means ++, Hierarchical
GMM
Anomaly/Outlier/Novelty Detection
PCA, t-SNE
Recommender Systems
Time Series Analysis
And/Or
Deep Learning
Neural Networks
Perceptrons
Neural Networks
Hidden Layers
Tensorflow
Keras
Forward and Back Propagation
Multilayer Perceptrons (MLP)
Callbacks
Tensorboard
Optimization
Hyperparameter tuning
Computer vision
Convolutional Neural Nets
Data Augmentation
Transfer Learning
CNN
CNN hyperparameters tuning & BackPropagation
CNN Visualization
Popular CNN Architecture - Alex, VGG, ResNet, Inception, EfficientNet, MobileNet
Object Segmentation, Localisation, and Detection
Generative Models, GANs
Attention Models
Siamese Networks
Advanced CV
Natural Language Processing
Text Processing and Representation
Tokenization, Stemming, Lemmatization
Vector space modelling, Cosine Similarity, Euclidean Distance
POS tagging, Dependency parsing
Topic Modeling, Language Modeling
Embeddings
Recurrent Neural Nets
Information Extraction
LSTM
Attention
Named Entity Recognition
Transformers
HuggingFace
BERT
1 Month
Machine Learning Ops
Streamlit
Flask
Containerisation, Docker
Experiment Tracking
MLFlow
CI/CD
GitHub Actions
ML System Design
AWS Sagemaker, AWS Data Wrangler, AWS Pipeline
Apache Spark
Spark MLlib
4 Months
The recorded lectures of Advanced Programming will be shared along with Teaching Assistant support (no live sessions)
Advanced Data Structures and Algorithms
Linked Lists
Stacks & Queues
Trees
Tries & Heaps
4 Months
Python libraries
Numpy, Pandas
Matplotlib
Seaborn
Data Acquisition
Web API
Web Scraping
Beautifulsoup
Tweepy
Probability and Applied Statistics
Probability
Bayes Theorem
Distributions
Descriptive Statistics, outlier treatment
Confidence Interval
Central limit theorem
Hypothesis test, AB testing
ANOVA
Correlation
EDA, Feature Engineering, Missing value treatment
Experiment Design
Regex, NLTK, OpenCV
Product Analytics
Framework to address product sense questions
Diagnostics
Metrics, KPI
Product Design & Development
Guesstimates
Product Cases from Netflix, Stripe, Instagram
3 Months
You can move to the advanced track only after you clear the transition test
Advanced Python
Python Refresher
Basics of Time and Space Complexity
OOPS
Functional Programming
Exception Handling and Modules
Math for Machine Learning
Classification
Hyperplane
Halfspaces
Calculus
Optimization
Gradient descent
Principal Component Analysis
Introduction to Neural Networks and Machine Learning
Introduction to Classical Machine Learning
Linear Regression
Polynomial, Bias-Variance, Regularisation
Cross Validation
Logistic Regression-2
Perceptron and Softmax Classification
Introduction to Clustering, k-Means
K-means ++, Hierarchical
3 Months each
You can pursue the Deep Learning specialisation after completing the Machine Learning specialisation or vice versa
Machine Learning
Machine Learning 1: Supervised
MLE, MAP, Confidence Interval
Classification Metrics
Imbalanced Data
Decision Trees
Bagging
Naive Bayes
SVM
Machine Learning 2: Unsupervised and Recommender systems
Intro to Clustering, k-Means
K-means ++, Hierarchical
GMM
Anomaly/Outlier/Novelty Detection
PCA, t-SNE
Recommender Systems
Time Series Analysis
And/Or
Deep Learning
Neural Networks
Perceptrons
Neural Networks
Hidden Layers
Tensorflow
Keras
Forward and Back Propagation
Multilayer Perceptrons (MLP)
Callbacks
Tensorboard
Optimization
Hyperparameter tuning
Computer vision
Convolutional Neural Nets
Data Augmentation
Transfer Learning
CNN
CNN hyperparameters tuning & BackPropagation
CNN Visualization
Popular CNN Architecture - Alex, VGG, ResNet, Inception, EfficientNet, MobileNet
Object Segmentation, Localisation, and Detection
Generative Models, GANs
Attention Models
Siamese Networks
Advanced CV
Natural Language Processing
Text Processing and Representation
Tokenization, Stemming, Lemmatization
Vector space modelling, Cosine Similarity, Euclidean Distance
POS tagging, Dependency parsing
Topic Modeling, Language Modeling
Embeddings
Recurrent Neural Nets
Information Extraction
LSTM
Attention
Named Entity Recognition
Transformers
HuggingFace
BERT
1 Month
Machine Learning Ops
Streamlit
Flask
Containerisation, Docker
Experiment Tracking
MLFlow
CI/CD
GitHub Actions
ML System Design
AWS Sagemaker, AWS Data Wrangler, AWS Pipeline
Apache Spark
Spark MLlib
4 Months
The recorded lectures of Advanced Programming will be shared along with Teaching Assistant support (no live sessions)
Advanced Data Structures and Algorithms
Linked Lists
Stacks & Queues
Trees
Tries & Heaps
3 Months
You can move to the advanced track only after you clear the transition test
Advanced Python
Python Refresher
Basics of Time and Space Complexity
OOPS
Functional Programming
Exception Handling and Modules
Math for Machine Learning
Classification
Hyperplane
Halfspaces
Calculus
Optimization
Gradient descent
Principal Component Analysis
Introduction to Neural Networks and Machine Learning
Introduction to Classical Machine Learning
Linear Regression
Polynomial, Bias-Variance, Regularisation
Cross Validation
Logistic Regression-2
Perceptron and Softmax Classification
Introduction to Clustering, k-Means
K-means ++, Hierarchical
3 Months each
You can pursue the Deep Learning specialisation after completing the Machine Learning specialisation or vice versa
Machine Learning
Machine Learning 1: Supervised
MLE, MAP, Confidence Interval
Classification Metrics
Imbalanced Data
Decision Trees
Bagging
Naive Bayes
SVM
Machine Learning 2: Unsupervised and Recommender systems
Intro to Clustering, k-Means
K-means ++, Hierarchical
GMM
Anomaly/Outlier/Novelty Detection
PCA, t-SNE
Recommender Systems
Time Series Analysis
And/Or
Deep Learning
Neural Networks
Perceptrons
Neural Networks
Hidden Layers
Tensorflow
Keras
Forward and Back Propagation
Multilayer Perceptrons (MLP)
Callbacks
Tensorboard
Optimization
Hyperparameter tuning
Computer vision
Convolutional Neural Nets
Data Augmentation
Transfer Learning
CNN
CNN hyperparameters tuning & BackPropagation
CNN Visualization
Popular CNN Architecture - Alex, VGG, ResNet, Inception, EfficientNet, MobileNet
Object Segmentation, Localisation, and Detection
Generative Models, GANs
Attention Models
Siamese Networks
Advanced CV
Natural Language Processing
Text Processing and Representation
Tokenization, Stemming, Lemmatization
Vector space modelling, Cosine Similarity, Euclidean Distance
POS tagging, Dependency parsing
Topic Modeling, Language Modeling
Embeddings
Recurrent Neural Nets
Information Extraction
LSTM
Attention
Named Entity Recognition
Transformers
HuggingFace
BERT
1 Month
Machine Learning Ops
Streamlit
Flask
Containerisation, Docker
Experiment Tracking
MLFlow
CI/CD
GitHub Actions
ML System Design
AWS Sagemaker, AWS Data Wrangler, AWS Pipeline
Apache Spark
Spark MLlib
4 Months
The recorded lectures of Advanced Programming will be shared along with Teaching Assistant support (no live sessions)
Advanced Data Structures and Algorithms
Linked Lists
Stacks & Queues
Trees
Tries & Heaps
×
Industry Recognized Certification.
6.
Will I receive a Data Science Certification upon completing this course?
Level up your career with Scaler’s Industry-Recognized Certification.
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7.
Can I try a demo class?
“Knowing us before growing with us” is our motto.
Attend a free class and get a feel of how your life with Scaler look like, understand our teaching patterns
8.
Who will teach me all this?
Only the best! Instructors are so amazing, you’d think they have superpowers
Our amazing Data Science instructors take live classes and resolve all your doubts on the go. We have the best pack from the industry!
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Your Mentors
Srikanth Varma
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Ajay Shenoy
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Harsh*t Tyagi
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Anant Mittal
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Mohit Uniyal
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Mudit Goel
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Prashant K Tiwari
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Sameer Shah
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Nitish Jaipuria
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Shan Mehrotra
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Sundaravaradhan
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Amit Singh
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Mohit Kukkarl
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Rahul Aggarwal
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Suraaj Hasija
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Suransh Chopra
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Thanish Batcha
Ex
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Vishwath parthasarathy
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Srikanth Varma
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Ajay Shenoy
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Harsh*t Tyagi
Ex
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Anant Mittal
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Mohit Uniyal
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Mudit Goel
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Prashant K Tiwari
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Sameer Shah
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Nitish Jaipuria
Ex
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Shan Mehrotra
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Sundaravaradhan
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Amit Singh
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Mohit Kukkarl
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Rahul Aggarwal
Ex
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Suraaj Hasija
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Suransh Chopra
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Thanish Batcha
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Vishwath parthasarathy
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Srikanth Varma
Ex
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- M.E C.S and Automation, IISC Bangalore
- I enjoy teaching and love solving problems that matter, by building products and services from the ground up. A life long learner, tinkerer and a team builder.
Ajay Shenoy
Ex
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- Ph.D , IISC Bangalore
- Research: My primary research interest is in applications of Machine Learning tools for Signal Processing. Other areas of interest include Pattern Recognition, Statistical Learning, Biomedical Signal Processing, Statistical Signal Processing, Compressed Sensing and Optimization.
Harsh*t Tyagi
Ex
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- LinkedIn Learning Instructor
- B.Tech Computer Science
- An engineer with amalgamated experience in web technologies and data science(aka full-stack data science).
- Mentored over 1000 AI/Web/Data Science aspirants.
- Designing data science and ML engineering learning tracks
- Previously, developed data processing algorithms with research scientists at Yale, MIT, and UCLA
Anant Mittal
Ex
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- University of Maryland
- B.Tech Computer Science , IIIT Hyderabad
- A self-motivated professional with proven skills in designing and developing data-driven and action oriented AI based solutions in Computer Vision and other varied business applications.
Mohit Uniyal
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- Data Scientist & Co-Creator at Coding Minutes
- Mentor@TensorFlow at Google Code-in
Mudit Goel
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- LinkedIn, Intuit, Coding Elements, Office of Principal Scientific Advisor to the Govt of India
- BS in Computer Science and Mathematics - State University of New York
- At LinkedIn and Intuit, Mudit was granted Data Science related patents by the US Government. He led Data Science teams at companies ranked among the most innovative companies in Data Science. Mudit founded Coding Elements, which was selected by Govt. of India to teach coding to 2 Million students. Mudit currently leads the Data Science and ML program at Scaler.
Prashant K Tiwari
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- CRED
- (B.Tech & M.Tech) in Information Technology from IIIT Gwalior
- Prashant did his Integrated Post Graduation (B.Tech & M.Tech) in Information Technology from IIIT Gwalior and currently working as a Data Engineer at CRED. Worked on different technologies and grasped different Software Development paradigms, languages, tools, and frameworks.
Sameer Shah
Ex
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- Media.net , WalmartLabs India
- MS Mathematics, IISC Bangalore
- An experienced data science professional adept at building end-to-end solutions to complex business problems. Has developed expertise in cross-domain, collaborative solution building due to a strong academic background coupled with continuous learning approach. Also, has a flair for leading and managing projects with a product mindset, proactive communication and interpersonal skills while maintaining the focus on the task at hand.
Nitish Jaipuria
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- Currently, I work as a Strategist in the Trust & Safety team at Google, wherein I build risk abuse infrastructure and pipelines for our NBU (Next Billion Users) suite of products.
- Additionally, I have worked on an NLP based product named Meena, with Google Brain’s Research Team
Shan Mehrotra
Ex
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- Compass, Salesforce ,Myntra
- Masters , Computer Science , IITB
- Senior Data Engineer at Compass. He has previously worked at Salesforce as a Data Engineer where he was responsible for creating a Data sync product.
- He has also worked at Myntra as a Senior Data Engineer in the Data Science department, where he was responsible for handling data pipelines, Azure wrappers, recommendations and size & fit based projects.
Sundaravaradhan
Ex
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- Ford Motor Company
- MS , Arizona State University
- Data Scientist at Ford Motor Company.
- Part of Material Planning & Logistics Analytics team providing solutions to stakeholders.
- Prior to this, He graduated from Arizona State University(ASU) with an MS in Industrial Engineering
Amit Singh
Ex
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- Ericson , TCS , Infosys
- B.Tech , Computer Science
- Microsoft Certified, Google & Cloudera (formerly hortonworks) Authorized Trainer
- Azure ML Engineer/Architect/Fundamental and Google Cloud Certified Cloud Architect Data Engineer having 1+ years of working experience in google cloud technology as technical architect
- 4 Years’ Experience in Software Development using C++, OCC, OpenGL,STL,XML,JNI, Core Java, Java Swing technologies and delivered multiple training on same
- An AWS/GCP certified DataOps/MLOps Engineer with extensive understanding of highly available and scalable architectures in cloud and on prem too.
Mohit Kukkarl
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- Gojek,Blinkit ( Previously known as Grofers )
- B.Tech , Thapar Institue of Engineering Technology
- A highly motivated analytics professional with 5 years of experience in delivering tangible insights in domains varying from supply chain planning to pharmaceutical sales operations.
Rahul Aggarwal
Ex
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- UnitedHealth Group , Infosys
- B.Tech Kurukshetra University
- Experienced Data Scientist with 8+ years of experience in Healthcare, Energy and Communication domains.
- killed in Predictive Modelling, Machine Learning, Deep Learning, Big Data Analytics, Requirement Gathering and Project Management.
- Proficient in Python, R, Hive/SQL, SparkSQL, PySpark, SparkR, MS Excel
Suraaj Hasija
Ex
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- Mastercard , GroundTruth , ZS
- PGP in Data Science and Machine Learning , IITB
- Deep technical expertise to generate power business insights from very large datasets with an aim to enable needle moving business impact through groundbreaking statistical analysis.
Suransh Chopra
Ex
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- Arcesium
- B.Tech Computer Science , DTU
- Software Engineer skilled in Machine Learning: Computer Vision & Natural Language Processing, Java, Python, C++, Data Structures and Algorithms, Docker, Kubernetes, Object-Oriented Programming, and Design Patterns. Deep Learning & Algorithms enthusiast.
Thanish Batcha
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- Amazon , Ford Motor Company , L&T Infotech
- B.Tech Velammal Institute of Technology
- Data scientist with an extensive experience working in wide range of problem across functions and diverse domains including Healthcare, Marketing, Automobile.
- Commendable understanding and implementation of building end to end Machine Learning solutions using various supervised/unsupervised state of the art algorithms to increase efficiency.
Vishwath parthasarathy
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- InMobi , Amazon
- B.Tech Anna University
- Data Scientist II at InMobi , Previously worked as Data Scientist at Amazon.
9.
Great, but what about the Scaler Data Science Course fee? Is it affordable?
Consider it a short-term investment for your long-term career growth!
Invest in your career and future, enroll with super affordable EMI options starting at Rs 8,628/- Try the course for the first 2 weeks - full money-back guarantee if you choose to withdraw.
View EMI Plans
EMI Options
You can find both no-cost EMI & standard interest EMI from our NBFC partners. See below a summary of their best plans (more details available at the time of payment)
Total Amount
Upfront Downpayment
Amount split over EMI
Duration (Months)
Monthly Payments
No Cost Emi
₹369,000
₹35,000
₹334,000
6
9
12
18
24
₹55,667
₹37,111
₹27,833
₹18,556
₹13,917
Standard Emi
₹369,000
₹35,000
₹334,000
36
60
₹12,339
₹8,628
Delivered via our EMI partners - Liquiloans, Eduvanz, EarlySalary, Avanse & Credit Fair
You can also choose to avail EMI options from your credit card providers.
Total Amount
Scholarship
Reduced Tution Fees
Upfront Downpayment
Amount split over EMI
Duration (Months)
Monthly Payments
No Cost Emi
₹250,0000
₹0
₹250,0000
₹35,0000
₹215,0000
12
9
12
₹35,0000
₹35,0000
₹35,0000
No Cost Emi
₹250,0000
₹0
₹250,0000
₹35,0000
₹215,0000
12
9
12
₹35,0000
₹35,0000
₹35,0000
Delivered via our EMI partners - Liquiloans, Eduvanz, EarlySalary, Avanse & Credit Fair
You can also choose to avail EMI options from your credit card providers.
10.
Can I connect with other top Data Scientists & ML Engineers?
Network with alumni and peers from top companies
Access Data Science related job opportunities from 600+ partner employers and exchange job opportunities with a 20k+ strong student community that will make you say Scaler Forever!
11.
Do you have any proof or reviews that your course works?
Our Proven Track Record shows that we walk the talk
Sumit Kumar
Application Developer at Udaan
A big shout out to my mentor Chandra Bhan Giri. I will always be grateful to you for your support and guidance. It would be impossible to count all the ways that you’ve helped me in my career.
Dolly Vaishnav
Software Developer at Ola
…The biggest shoutout to my mentor Krunal Parmar for constantly pushing & guiding me throughout the journey. He is the best mentor I could ever get…
Ready to become a data science and machine learning expert? Book a live class with Srikanth Varma and start your journney!
Book Live Class Request Callback
Scaler Data Science Training FAQ’s
Program
This Data Science course is designed for everyone, even if you have no coding experience. We offer a Beginner module that covers the basics of coding to get you started.
Scaler's Data Science and Machine Learning program is considered one of the best data science courses because-
- Covers all essential data science topics, ensuring a holistic learning experience.
- Emphasis on hands-on projects equips students with real-world skills, setting them up for success in the field.
- Industry experts as instructors provide invaluable insights and knowledge.
- Scaler's industry connections and placement assistance enhance job prospects.
- The program caters to diverse backgrounds, offering flexibility in learning for all.
Yes, you have the flexibility to attend Scaler’s Data Science online course on a part-time basis. In case you miss a live class, you can always access the recorded sessions. You can also take a break of up to 3 months, all this within the course duration.
While designing the Scaler Data Science course, we did not put any limit on the duration. We included each and every concept that is important for making you a strong Data Scientist and ML Engineer. The course turned out to be 15 months long with more hands-on experience.
Live classes are held 3 times a week, on alternate days, primarily in the late evening or night on weekdays to accommodate working software engineers. Weekend timings are flexible.
While designing the Scaler Data Science course, we did not put any limit on the duration. We included each and every concept that is important for making you a strong Data Scientist and ML Engineer. The course turned out to be 15 months long with more hands-on experience.
Notice that the course is quite rigorous; each week you will have 3 Live lectures of 2.5 hours each, homework assignments, business case project, and discussion sessions. This allows us to cover the entire depth and breadth of Data Science & Machine Learning, as much as is required for you to succeed in the role.
The total Data Science course fees is ₹369,000. With EMI, this can drop as low as ~INR 8,628/month (equivalent to your monthly grocery bill!)
Absolutely! Scaler offers a top-notch data science course designed to equip you with the skills and knowledge needed to excel in this field. Our program emphasizes hands-on learning with real-world projects and 1:1 mentorship from industry experts. We believe in providing practical experience that translates directly to the workplace. With our comprehensive curriculum and career support services, Scaler is an excellent choice for anyone looking to kickstart or advance their career in data science.
Why Choose Scaler for Data Science?
- Get 1:1 Mentorship from Expert Data Scientists and ML Engineers!
- Up-to-date curriculum with the fast-evolving Data Science and ML field.
- Master essential tools and languages used in data science and machine learning.
- Get Expert career guidance to help you navigate your path in data science.
Eligibility
Yes, there is an eligibility test called the Scaler entrance test for enrolling in Scaler's Data Science program.
In Scaler's Data Science certification course, you'll acquire a wide range of skills, including:
- Beginner skills in Tableau, Excel, SQL, and Python.
- Data analysis and visualization using Python libraries, probability, and statistics.
- Foundations of machine learning, deep learning, and neural networks.
- Specializations in either machine learning or deep learning.
- Advanced knowledge in machine learning operations, data structures, and algorithms to excel in the field.
Scaler’s Data Science and Machine learning program is open to both freshers and working professionals. who are comfortable and confident with 10 standard aptitudes and mathematics.
A coding background is not required to enroll in this Data Science training. You can start from the Beginner module in which we will cover the basics of coding.
In fact, prior knowledge in Data Science or ML is also not needed. We will cover all the relevant topics from scratch.
The only prerequisite is that you should have a basic understanding of 9th and 10th-grade school maths - just the basics, nothing advanced. Still, we will cover these topics in class, but some prior knowledge would be helpful.
Data Science
Data science is a field of computer science that uses various algorithms, methods, and machine learning to uncover hidden and meaningful insights in both structured and unstructured data.
Data science can be challenging, as it requires a solid understanding of mathematics, statistics, and programming. However, with dedication and the right resources, it's accessible to those willing to learn.
A data scientist is an expert in data science who specializes in collecting and analyzing large amounts of data from diverse sources. They use their skills in mathematics, statistics, and computer science to help organizations make informed decisions based on data analysis.
To become a Data Scientist, follow these steps:
- Learn the fundamentals of programming and statistics.
- Acquire knowledge in machine learning and data analysis.
- Build a strong portfolio of projects.
- Pursue relevant courses.
- Apply for Data Scientist positions.
A Data Scientist designs new data approaches, while a Data Analyst interprets existing data. Data Scientists create innovative ways to collect and analyze data, while Data Analysts extract insights from available data.
Job and Career
Yes, Data Science is an excellent career choice in 2024. The field is growing rapidly, with high demand for professionals due to its continued relevance and the increasing importance of data-driven decisions.
After completing the data science course, you can explore various job roles, including:
- Business Analyst
- Data Analyst
- Data Scientist
- Big Data Engineer
- Data Engineer
- Machine Learning Engineer
- Data Architect, and many more.
Top companies like Amazon, Google, IBM, Oracle, Deloitte, Facebook, Microsoft, Wipro, Accenture, Visa, Bank of America, and Fractal Analytics are actively hiring data scientists.
At Scaler, we are committed to supporting our students in their career journeys through extensive placement support and our network of 900+ partner companies. While we do not provide job guarantees, we offer valuable resources and training to improve job prospects.
Our students benefit from personalized career guidance, regular mentorship, interview preparation assistance, resume building support, and mock interviews conducted by industry experts. The active Scaler community, with over 40,000 members, provides networking opportunities and continuous support.
Notably, our DSML alumni have secured a median salary hike of 110% and medium CTC of INR 18 lakhs per annum.
Take a look at the Scaler Career Assessment Report audited by B2K Analytics for more insights.
Certification
To earn Scaler's Data Science certification, you need to successfully complete all the required course modules, assignments, and projects. You'll be assessed based on your performance throughout the program.
Scaler's Data Science certification is a lifetime certification, meaning it doesn't expire. Once you earn it, you can proudly showcase your expertise in data science throughout your career.
We are providing certificates to all the learners after the end of the program
Scaler's Data Science certification is highly regarded in the industry. It's recognized for its comprehensive curriculum and hands-on approach, making you job-ready.
Lectures
If you miss a lecture, you can still watch it offline, and it won't affect your attendance.
Yes, you can access course materials and lectures for up to 6 months after completing the course.
If you find it challenging to balance your job or schedule with class timings, you can catch up by watching the recorded lectures as classes are held three times a week on alternate days.
Scaler’s data science program is instructor-led, ensuring you have guidance and support throughout your learning journey.
All the Maths required for understanding and implementing algorithms will be covered in this Data Science training (Probability, Statistics, Linear Algebra, Calculus, Coordinate Geometry).
Community
Scaler offers multiple support channels for students, including whatsapp groups for collaboration, dedicated problem-solving support on the dashboard, and Scaler support through chat, and phone for any concerns or queries.
Yes, there is a Scaler community where students can interact and collaborate with each other.
The scaler community has people working worldwide. The bottleneck is in getting a visa sponsorship. Many companies based in India offer opportunities for their high-performing employees to work on international data science projects and relocate. Some international companies also hire directly in India and ask to relocate for jobs. However, with the surge in WFH, this trend may be ebbing. However, you can continue applying for remote data science jobs based outside India via LinkedIn.
Opportunities
For learners who show interest in publishing in the data science domain, we would be happy to provide mentorship and support.
Masters and Ph.D.s are typically asked for Research-focused data science roles. Most companies do not require a Master's degree for a Data Science role.
😎 Look who is famous!
Scaler Data Science and Machine Learning is the talk of the town!
Scaler Acquire edtech platform applied roots to scale up its data science, AI and ML programmes to a wider base of tech learners
Times Of India
Scaler has launched a new program for engineers in data science and Machine learning which will have a foundation of DSA, followed by mathematics, big data, data mining, machine learning, deep learning
The Economic Times
Building a better India with data science and machine learning
The Hindu
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