Data Science Training Program
A Program to Excel in Data Science Career
Program Overview
About Feligrat Training Programs
- Industry Expert Guidance
- Career Assistance
- Advance Practical Learning
- Endless Job Opportunities
Evolve into an Exceptionally well-versed Data Science Profession
Benefits of Data Science Training
Feligrat Covers both curriculum and advanced tools such as PySpark, SQL, GIT, Data Wrangling, and MLOps, these sessions will ensure that you have all the knowledge and skills you need to be successful.
Career Advancement
The program is curated with a team of Expert Data Scientists to guide your journey.
Live Virtual Session
Data science face-to-face training customized to live online classes aligned with your schedule.
Hands-on Experience
Take advantage of a data science course for beginners and Practice on Industry projects.
Placement Assistance
One of the best Data Science training with Placement consists of top hiring companies.
Learning Support
In our Online Data Science Bootcamp, Get all the learning materials & recording in one single place.
Real World Approach
We take an ideal approach toward real-world challenges and assist candidates with a mindset.
Demand Of Data Scientist
DS professionals are in high demand in the industry. Companies need certified and eligible candidates to analyze the data and assist with data-driven decisions for businesses, helping them to scale in the future.
Be the Machine Learning Engineer, Decision Scientist, or Big Data Specialist of a company.
Course Outline
Learning Path of Data Science
Program Cohorts includes Aspiring professionals of any educational background with an analytical frame of mind is suited to pursue the Data Scientist Master’s Program
Chapter 1 – Python Basics
Chapter 2 – Python Data Structures
Chapter 3 – Python Programming Fundamentals
Chapter 4 – Working with Data in Python
Chapter 5 – Working with NumPy Arrays
Chapter 1 – Data Science Overview
Chapter 2 – Data Analytics Overview
Chapter 3 – Statistical Analysis and Business Applications
Chapter 4 – Python Environment Setup and Essentials
Chapter 5 – Mathematical Computing with Python (NumPy)
Chapter 6 – Scientific computing with Python (Scipy)
Chapter 7 – Data Manipulation with Pandas
Chapter 8 – Machine Learning with Scikit–Learn
Chapter 9 – Natural Language Processing with Scikit Learn
Chapter 10 – Data Visualization in Python using matplotlib
Chapter 11 – Web Scraping with BeautifulSoup
Chapter 12 – Python integration with Hadoop MapReduce and Spark
Chapter 1 – Introduction to Artificial Intelligence and Machine Learning
Chapter 2 – Data Wrangling and Manipulation
Chapter 3 – Supervised Learning
Chapter 4 – Feature Engineering
Chapter 5 – Supervised Learning-Classification
Chapter 6 – Unsupervised learning
Chapter 7 – Time Series Modelling
Chapter 8 – Ensemble Learning
Chapter 9 – Recommender Systems
Chapter 10 – Text Mining
Chapter 1 – Getting Started with Tableau
Chapter 2 – Core Tableau in Topics
Chapter 3 – Creating Charts in Tableau
Chapter 4 – Working with Metadata
Chapter 5 – Filters in Tableau
Chapter 6 – Applying Analytics to the worksheet
Chapter 7 – Dashboard in Tableau
Chapter 8 – Modifications to Data Connections
Chapter 9 – Introduction to Level of Details in Tableau (LODS)
Chapter 1 – Fundamental SQL Statements
Chapter 2 – Restore and Back-up
Chapter 3 – Selection Commands: Filtering
Chapter 4 – Selection Commands: Ordering
Chapter 5 – Alias
Chapter 6 – Aggregate Commands
Chapter 7 – Group By Commands
Chapter 8 – Conditional Statement
Chapter 9 – Joins
Chapter 10 – Subqueries
Chapter 11 – Views and Index
Chapter 12 – String Functions
Chapter 13 – Mathematical Functions
Chapter 14 – Date – Time Functions
Chapter 15 – Pattern (String) Matching
Chapter 16 – User Access Control Functions
Chapter 1 – Introduction to Business Analytics
Chapter 2 – Introduction to R Programming
Chapter 3 – Data Structures
Chapter 4 – Data Visualization
Chapter 5 – Statistics for Data Science I
Chapter 6 – Statistics for Data Science II
Chapter 7 – Regression Analysis
Chapter 8 – Classification
Chapter 9 – Clustering
Chapter 10 – Association
IT Professionals
Analytics Managers
Business Analysts
Banking and Finance Professionals
Marketing Managers
Supply Chain Network Managers
Beginners or Recent Graduates in Bachelors's or Masters Degree
Data Science Certification
Frequently Asked Question
Data Science Training FAQ for the candidates to resolve queries.
Data Science is a field that extracts valuable insights from information/data and guides businesses to make data-driven decisions. It acts as a success compass for business directions.
- According to IBM predictions there will be 137,630 data science job openings in India by 2025!
- According to U.S. Bureau of Labor Statistics: “Employment of data scientists is projected to grow 36% from 2021 to 2031, much faster than the average for all occupations
We provide placement for candidates who qualified and certified from Feligrat as a data science professional. We are located in Mumbai hence you can visit us and check for our Data science courses in Mumbai with placement
The data science training program is tailored for freshers as well working professionals. We have set detailed customization according to your background. You can definitely bet on this data science course for beginners.
No. Data Science Field is evolving and companies are looking for qualified data scientist who can help them to make data-driven decision.
Anyone who has interest in technical as well as analytical approach can become data scientist. There is no stream criteria but you have to be well-versed with mathematics and coding scenarios.
Feligrat is a place where you should complete your data science course and get placed in MNC’s. We believe that Wonders happen when you are at right environment at right time.
Our Data science course duration will be of 120 HRS with 4 capstone Projects taken by leading industry data science experts.