Experience theoretical learning in classroom and practical learning during your internship.
Become a full-stack data scientist by learning each aspect of the data science ecosystem.
Take advantage of the holistic learning experience by interacting with peers and team projects
90% batch has been placed with 2 months still remaining for the completion of the batch.
On average, a bootcamp student saw an increase of 250% salary jump.
More than 30 companies have participated in Analytics Vidhya’s hiring drives
Get the right knowledge and experience required to get your dream data science job.
Deep dive into the world of data science with the right blend of tools, techniques and projects.
Transition into data science early on in your career and start young in the world of data science.
17+ Modules starting from basics like Excel to the most advanced machine learning topics
Overview Data Science and Application
Common terminologies of Data Science
Various roles within Data Science
Essential Stages of Data Science Life Cycle
Organizational challenges while building Data Science projects
Problem Formulation and Framework to choose right problem statement
Hypothesis Building and Framework
How to Build Comprehensive Hypothesis set
Excel Basics, Formulas and Functions
Excel Charts, Pivot Tables, Sort, Filter, What-if Analysis tool
Build business simulation using Excel
Basics of databases
ACID and BASE properties of a database
Working with SQL, Extract data from databases containing multiple tables
Performing Data Analysis using SQL
Loading datasets and establishing table relationships
Work with different type of charts and dashboards
Working with Map visualizations and other advanced charts with drill down functionalities
Working with power query for data manipulation
Writing DAX expressions
Python Basics Programming (Conditional, Looping, Functions)
Pandas, Matplotlib, Seaborn, regular expression, beautifulsoup
Good programming practices (testing, debugging, assertions, exception handling)
Get familiar with functional programming and its use cases
Understand the concepts of Object Oriented Programming (Inheritance, encapsulation)
Learn about version control and working with github
Connecting with databases using python
Public Vs Private Cloud
IaaS vs PaaS Vs SaaS
AWS Global Infrastructure
AWS Compute Services - EC2, AWS Lambda
AWS Storage Services - S3, DynamoDB, RedShift
AWS Security Policies
Monitoring & Analysis - AWS CloudWatch
Univariate, Bi-variate and Multivariate analysis
Work with different type of tests like t-test, z-test, chi-square test, anova
Work with Missing values, outliers, data pre-processing
Learn Important ML Basics Concepts (Train, Test, Validate, Bias , Variance, Overfitting, Underfitting)
Work with Evaluation metrics (Classification and Regression both)
Work with different validation techniques
Perform data cleaning and Preprocessing
Linear Models, Decision Tree, k-NN
Math Behind each Machine Learning Algorithm
Building Classification and Regression Models
Hyperparameter Tuning to improve model
Introduction to unsupervised learning and clustering
Working of clustering algorithms (k-means clustering)
Evaluation metrics for unsupervised learning problems
Understand feature engineering for structured and unstructured data
Perform feature extraction, generation and transformation techniques
Explore the basic and advanced ensemble techniques (rank averaging, random forest and more)
Challenges & Applications of Big Data
Introduction to Distributed Computing
RDDs & DataFrames
Understanding Spark Execution
Building Classification & Regression Models
Building ML Pipelines
SQL vs NoSQL databases
Different types of NoSQL databases
Querying, Aggregation & Indexing in MongoDB
Replicate & Share data in MongoDB
Exploring time series data and dealing with date-time variable
Learn Basic Forecasting algorithms (naive approach, simple average, moving average)
Work with Exponential smoothing algorithms (Simple, double, holts winter)
Work with Advanced forecasting algorithms (ARIMA, SARIMA, Prophet)
Introduction to NLP and its applications
Handling Text Data (Cleaning and Pre-processing)
Information Extraction and Retrieval from text
Feature Engineering from textual data
Introduction to Deep Learning
Introduction to Neural Networks
Activation Function, Optimizers, Loss Functions
RNN, LSTM, GRU
Introduction to Model Deployment
Deploying Your First Machine Learning models
Deploying ML Learning model using Streamlit + AWS
Deploying Image Classification model using Streamlit + AWS
Customer retention is a crucial aspect for any organization. Learn to use the Data Science Techniques for predicting the propensity of customer churn for a Bank.
To improve the efficiency of taxi dispatching systems, it is important to be able to predict how long a driver will have his taxi occupied. Build Machine Learning Models to accurately predict trip duration for taxi trips in New York City.
Work on a dataset of FIFA19 players and do descriptive analytics on it. Go through the thought process of how data is understood, transformed into a useful format and how we get answers and insights from our data.
Fatalities due to traffic delays of emergency vehicles such as ambulance & fire brigade is a huge problem. Use Deep Learning Techniques and design a system for classifying a vehicle into an emergency and non emergency category.
Apply for the Data Science Bootcamp program 2021 by filling up the registration form.
Take the Assessment tests, assignments and undergo the interview round.
Get started on your journey to become a industry ready data scientist
Candidates can pay the program fee through Netbanking, Credit/Debit cards, Cheque or DD. Also, with our corporate financial partnerships avail education loans at 0% interest rate*.
Associate Consultant in KPMG
Associate Consultant (Data Scientist), KPMG
AM- Analytics at PaisaBazaar
Hear the story of Sarthak, who went from being a fresher to AM - Analytics at Paisabazaar, India’s largest fintech company.
Get a glimpse of Kamaldeep’s journey into the field of data science and how he managed to grab one of the hottest roles in the industry
Hear the story of Ashwin, who converted his experience and transitioned into data science successfully.
Get a glimpse of Kaushal’s story, who took a leap of faith which was worth it.