Scaler Data Science & Machine Learning Program - Advanced by Scaler Academy: Fee, Duration, How to Apply

Quick Facts

particular	details
Medium of instructions English	Mode of learning Virtual Classroom	Mode of Delivery Video Based

Course overview

The Scaler Data Science & Machine Learning Program - Advanced offered by Scaler is an 7 months program based on the level of students. During live courses, students will learn to work on real-world industrial projects and receive real-time feedback from instructors. Learners will communicate with their peer learners to debate various ideas.

The Scaler Data Science & Machine Learning Program - Advanced teaches students a practical approach by sample projects such as developing the optimal strategy for giving discounts and coupons based on consumer behaviour, and experimenting with various driving routes to reduce wait times. estimate when meals will arrive at customers' homes by using various data and models of Artificial Intelligence, analyze millions of chat conversations using AI to detect fraud.

Students are chosen for beginner/Intermediate/Advanced level based on the 30 minutes MCQ test. Beginner and Intermediate levels cover certain basic subjects that Advanced level students do not need to know about. The Data Science and Machine Learning - Advanced syllabus covers various topics such as Advanced Programming, Data Analytics, Machine Learning, Data Science, Statistical Analysis, Deep Learning, Big Data.

Course and certificate fees

certificate availability

Yes

certificate providing authority

Scaler Academy

Who it is for

Anyone who wants to learn about data science and machine learning can join the course.

Eligibility criteria

Anyone graduated in 2020 or earlier is eligible to apply for the course.

Certification Qualifying Details

Students will have to complete the course curriculum along with submitting assignments and projects. Candidates will have to qualify a certain parameter set by the course provider to get the Scaler Data Science & Machine Learning Program - Advanced certification.

What you will learn

Machine learning Knowledge of python Knowledge of numpy

After completing the Scaler Data Science & Machine Learning Program from Scaler, students will learn about Numpy, Panda, Python, SQL, Flask. Candidates will also learn about data science and machine learning engineering, Data Wrangling, Predictive modelling, NLP, computer vision, neural networks, Python Spark. Students will grasp advanced programming knowledge.

The syllabus

Module - 1 Foundations of Machine Learning and Deep Learning

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

Module - 2 Specializations

Machine Learning

Machine Learning 1: Supervised

MLE, MAP, Confidence Interval
Classification Metrics
Imbalanced Data
Decision Trees
Bagging
Naive Bayes
SVM

Machine Learning

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

Deep Learning

Neural Networks

Perceptrons
Neural Networks
Hidden Layers
Tensorflow
Keras
Forward and Back Propagation
Multilayer Perceptrons (MLP)
Callbacks
Tensorboard
Optimization
Hyperparameter tuning

Deep Learning

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

Module - 3 Machine Learning Ops

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

Module - 4 Advanced Data Structures and Algorithms

Advanced Data Structures and Algorithms

Linked Lists
Stacks & Queues
Trees
Tries & Heaps

Admission details

To enrol in the Scaler Data Science & Machine Learning Program from Scaler, follow the steps mentioned below:

Step 1. Open the official Scaler course page by following the link given below.

(https://www.scaler.com/data-science-course/)

Step 2. Click the ‘Apply Now’ Button to proceed

Step 3. Fill in the personal details and register your account.

Step 4. Candidates will have to give a 30 minutes MCQ test, students scoring marks above advanced level will be eligible for enrolling in the advanced level of the course, otherwise they will have the option to join as a beginner or Intermediate.

Step 5. Pay the course fee and start the program.

Scholarship Details

Candidates will get a scholarship of up to Rs 25,000, and there are also very inexpensive EMI and financing alternatives available.

How it helps

Candidates pursuing Scaler Data Science & Machine Learning Program from Scaler will be benefited in the following ways:

Learn about data analytics, deep learning, advanced programming, machine learning with industry experts.
Candidates will get a course completion certificate from Scaler after completing the program.
The training assists individuals in preparing for job searches and interviews by optimizing resumes and conducting mock interviews.