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Is your 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

4 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
4 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
Beginner Python
  • Flowcharts, Data Types, Operators
  • Conditional Statements & Loops
  • Functions
  • Strings
  • In-built Data Structures - List, Tuple, Dictionary, Set, Matrix Algebra, Number Systems
Read Next: Module 2 - Data Analysis and Visualization
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
Read Next: Module 3 - Foundations of Machine Learning and Deep Learning
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
Read Next: Module 4 - Specializations
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
Read Next: Module 5 - Machine Learning Ops
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
Read Next: Module 6: Advanced Data Structures and Algorithms
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
Read Prev: Module 1 - Beginner Module
Download Curriculum
4 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
Beginner Python
  • Flowcharts, Data Types, Operators
  • Conditional Statements & Loops
  • Functions
  • Strings
  • In-built Data Structures - List, Tuple, Dictionary, Set, Matrix Algebra, Number Systems
Read Next: Module 2 - Data Analysis and Visualization
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
Read Next: Module 3 - Foundations of Machine Learning and Deep Learning
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
Read Next: Module 4 - Specializations
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
Read Next: Module 5 - Machine Learning Ops
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
Read Next: Module 6: Advanced Data Structures and Algorithms
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
Read Prev: Module 1 - Beginner Module
Download Curriculum
Programme Fee - Starting at INR 7,200/month. No cost EMI options available
INR 2,50,000 (including GST)
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Kushal V Mahajan
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Suryanshu Gupta
scaler
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Mohini Bansal
linkedin
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And the most important part, the mock interviews with my mentor, made me more confident day by day.
Have more questions? Contact us and get all your questions answered by our expert Data Science counsellor. Call us on 08045579578
Have more questions? Reach us at 08045579578