Data Science Certification Ahmedabad

Data science training course with full-time certification

In recent times, technology like big data, AI, are being used everywhere. Data science is capable of turning the imagination to reality. Hence, it is imperative to opt the Data science learning courses that Highsky IT, Ahmedabad offers.

What is data science training?

Data science is a mixture of algorithms, statistics, and includes massive aspects of machine learning elements. The principal goal of studying data science is to create unstructured data for better storage in a small space. The traditional data that was used previously was structured and smaller in size. With data science, the data used now are most of the time unstructured or sometimes semi-structured.

Opting for a data science training can help students stretch out their fields of knowledge and implementation. After the training, one will be able to write expert codes in R programming languages along with specific expertise in data transformation and analysis.

What to learn in training?

Anyone keen to know about business intelligence, big data, or a professional statistician, information architect, developers, can take up the data science training for a better job profile or research experience. On our data science training course, one will learn the history of data science & its progress. The course starts with a good introduction and gradually enters the advanced levels, including the fundamentals of big data mining, data manipulation, and the underlying structures.

Why choose us?

Highsky IT is giving you a chance of becoming a industry leader by opting for a simple data science learning course in Ahmedabad. Our facilities focus on advanced learning through our digital classroom. Our Faculties for data science learning training are experts in the field. The main motive is to provide eligible education to our students.

Course Duration: 45 days

1. Data Science Overview

Introduction to Data Science
Different Sectors Using Data Science
Purpose and Components of Python
Data Science and visualization

2. Data Analytics Fundamentals

Data Analytics Process
Exploratory Data Analysis (EDA)
EDA – Quantitative Technique
EDA – Graphical Technique
Data Analytics Conclusion or Predictions
Data Analytics Communication
Data Types for Plotting
Data Types and Plotting

3. Statistical for Business Applications

Introduction to Statistics
Statistical and Non-statistical Analysis
Major Categories of Statistics
Statistical Analysis Considerations
Population and Sample for Statistical Data
Statistical Analysis Process
Data Distribution & Dispersion
Histogram for python
Correlation and inferential Statistics

4. Python Environment Setup

Python Anaconda
Installation of Anaconda Python Distribution (contd.)
Data Types with Python
Basic Operators and Functions

5. Mathematical Computing using NumPy

Introduction to NumPy
Creating and Printing an ndarray
Class and Attributes of ndarray
Basic Operations
Activity-Slice It
Copy and Views
Mathematical Functions of NumPy

6. Scientific Computing using SciPy

Introduction to SciPy
SciPy Sub Package – Integration and Optimization
Calculate Eigenvalues and Eigenvectors
SciPy sub Package – Statistics, Weave and IO

7. Data Manipulation using Pandas

Introduction to Pandas
Understanding DataFrame
View and Select Data Demo
Missing Values
Data Operations
File Read and Write Support
Pandas Sql Operation

8. Machine Learning using Scikit-Learn

1. Supervised Learning Model Considerations
2. Scikit-Learn
3. Supervised Learning Models – Linear Regression
4. Supervised Learning Models – Logistic Regression
5. Unsupervised Learning Models
6. Pipeline
7. Model Persistence and Evaluation

9. Natural Language Processing using Scikit Learn

NLP Overview
NLP Applications
NLP Libraries-Scikit
Extraction Considerations
Scikit Learn-Model Training and Grid Search

10. Data Visualization using matplotlib

Introduction to Data Visualization
Line Properties
(x,y) Plot and Subplots
Types of Plots

11. Data Visualization Advance

· Data Visualization using Seaborn
· Data visualization over large scale data