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FELIGRAT
FELIGRAT
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
We cover every essential aspect of SAP QM, including quality planning, inspection processes, quality control, regulatory compliance, and integration with other SAP modules like MM, PP, and SD.
With a cutting-edge and rigorous SAP QM training curriculum, along with hands-on projects, you will gain the expertise to drive quality excellence and make informed decisions that enhance business operations and ensure product quality at every stage.
Learn essential SAP QM concepts such as quality planning, inspections, quality control, and regulatory compliance. Our training involves mastering tools and software like SAP S/4HANA, SAP Fiori, and SAP BW to analyze and manage quality data effectively.
SAP QM is a rapidly growing field with high demand across various industries, including manufacturing, automotive, pharmaceuticals, and technology. Upon completing this SAP QM training, secure a position with top MNCs in the quality management domain
The SAP QM course covers core concepts and advanced tools, equipping you with the knowledge and skills needed for success in quality management using SAP.
Career Advancement
Live Virtual Session
SAP QM face-to-face training customized to live online classes, aligned with your schedule.
Hands-on Experience
Take advantage of our SAP QM course for beginners and practice on real industry projects.
Placement Assistance
One of the best SAP QM training programs with placement opportunities at top hiring companies.
Learning Support
In our Online SAP QM Bootcamp, get all the learning materials and recordings in one convenient place.
Real World Approach
Experience a unique learning journey at Feligrat that combines theoretical knowledge with practical, hands-on experience, paving the way for a successful career in SAP.
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.
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.
