Course - Key highlights
Learn – Data Engineering & Data Analysis Courses in Coimbatore
Less than five years of experience are sought by 70% of Data Science job openings. Our courses in Data Science, Data Engineering with Python, Data Science with R, and Data Analytics with Power BI are designed to cater to the growing demand for skilled professionals in this domain. The acquisition of skills in data science and data analytics can unlock diverse career prospects in areas including data analysis, business intelligence, and decision-making.
Course objective
Our data science courses in Coimbatore provide students with the knowledge they need to become proficient in their chosen field of Data Science. Our training programmes aim to bridge the gap between industry demands and aspiring professionals’ current skill set, assisting them in achieving their career objectives. We provide comprehensive training to prepare students for a rewarding career in data science.
Key Topics Covered
- Python fundamentals
- Standard Libraries
- Introduction to Power Bi
- Connecting and Shaping
- Creating Data Model
- Calculated Fields and Dax
- Visualization
- Artificial Intelligence in power Bi
- Power Bi Optimization
Data Analytics using Power BI
- Appending data
- Merge Queries & M Language
- Objects, bookmarks, slicers
- Tables, MAPS, charts
- Text functions
Data Science
- Data Analytics & its Methodologies
- Data Mining
- Data Visualization
- SAS & SPSS
- Supervised learning algorithm
Data Science & Data Engineering using Python
- API libraries
- Clustering & classification
- Data Distribution & correlation
- Decision free
- Exploratory Data Analysis
- Forecasting
- Text mining
Data Science using R
- Clustering, Classification
- Decision Tree and Forecasting
- R Programming
- Regression Analysis
- Statistics & Probability
Who is this Course suitable for?
- Aspiring data scientists
- Software developers
- IT professionals
- Analytics professionals
- Graduates looking for a career in AI
This course covers both fundamental and advanced machine learning concepts, such as data preparation, feature engineering, model selection, and optimisation. You will learn to use and implement popular machine learning algorithms such as regression, clustering, and decision trees in Python and R.
