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About Analytics Vidhya

Location: Online

Data Science Immersive Bootcamp Program by Analytics Vidhya is a Job Guaranteed* Training Program. It is a Live Instructor Led Online Program(500+ hours) led by Industry Experts on Data Science, Data Engineering and Cloud Computing. The program comes... Read More


Data Science Immersive Bootcamp

Cost: $3,500
Duration: 30 weeks
Locations: Online
Course Description:


1. Introduction to Data Science and understanding the stages of Data Science lifecycle
Get an overview of what Data Science is and how organizations leverage it - Understanding the Stages of Data Science Lifecycle

2. Problem Formulation and Storytelling using Excel
Formulating Business Problem to Data Science Challenge - Best practice to perform hypothesis generation - Create data stories to create business insights

3. Build Data Stories using SQL
Get proficiency with SQL - Work with high volume of structured data

4. Build Data Stories using PowerBI
Building data stories and creating impactful reports and dashboards for a given dataset using PowerBI

5. Python for Data Science
Get familiar with python programming - Able to read/write files from /to various sources

6, Software Engineering Fundamentals
Master the advanced python programming concepts - Get familiar with functional and object oriented programming - Able to work with shell/terminal commands - Familiarity with github and working with databases

7. Cloud Computing
Understanding the Fundamentals of Cloud Computing - Get familiar with Amazon Web Services (AWS)

8. EDA and Statistics
Perform univariate and multivariate analysis and generate business and statistical inferences

9. Getting started with Machine Learning
Understand Machine Learning basic concepts - Build and Improve ML solutions for regression and Classification models

10. Unsupervised Machine Learning Models
Understand the concept of unsupervised learning - Get familiar with important unsupervised learning algorithms

11. Feature Engineering and Ensemble Learning
Learn about feature engineering and its importance in data science - Explore the different feature engineering techniques - Understand the concept of ensemble learning and build ensemble models

12. Building Scalable Models
Understand the Architecture of Apache Spark - Build ML models using Spark - Automate the ML workflow using Spark ML Pipelines

13. Working with NoSQL DataBases
Basic understanding of different types of NoSQL databases - Get proficiency with MongoDB

14. Time Series Forecasting
Learn to work with time series problems - Explore the time series forecasting algorithms

15. Getting started with Natural Language Processing (NLP)
Understand what Text data comprises of and how to work with it -Start right from loading text data, pre-processing it to extracting features for solving complex NLP tasks

16. Basics of Deep Learning
Introduction to Deep Learning -Understanding different types of neural networks -Exploring different Deep Learning frameworks

17. Model Deployment
Deploying Machine Learning and Deep Learning models using Streamlit -Deploying Machine Learning and Deep Learning models using Amazon Web Services (AWS)

NoSQL, Apache, Python, Machine Learning, SQL, AWS, Data Science, Cloud Computing

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