Data Science

Zeetron Network is one of the best Data Science training companies in Jaipur with experienced professionals and a dedicated team. Our data science training in Jaipur will cover the complete standard module of Data Science and related technical topics that is important for students and professionals to know to become a dedicated professional or data scientist for multiple companies. Zeetron Networks’ Data Science online and offline training in Jaipur includes the complete syllabus like Python, basics of R, Statistics, Internal Statistics, Regression, and ANOVA, etc.

We will teach you those things in python which are important to learn in order to get recognition as an expert professional of python in the IT sector.

Zeetron Network is the right place for data science certification training just because we are having Real-Time Expert Trainers, Certificate, Training & Project based internship in Data Science, affordable fee schedule, flexibility in services as well as complete placement assistance for students. We are the only data science internship company in Jaipur which is more focused on industrial learning and quality teaching to our students.

The learning of Data Science will lead a person to groom his professional career into multiple related technologies like Machine Learning, Artificial Intelligence using Big Data Hadoop as a data scientist or data analyst in Jaipur

Data Science Learning Outcomes
- Develop hard skills in Data Science like Python, R Programming, Statistics, Machine Learning, Artificial Intelligence, Tableau, Deep Learning, Neural Networks, TensorFlow, Unix, Git, SQL.
- Our Courses integrate real-world hands-on training with case studies & projects using Datasets from companies like Amazon, Facebook, Adobe, Walmart, etc.
- Work on Real Projects, Build a Portfolio, Attend Interviews and Get Hired.
- Certified Data Science Trainer with Years Real Time Industry Experience.
- Best faculty with excellent Lab Infrastructure along with detailed course material.
- Prepare your CV/Resume to attend Interviews and securing a Job.
- We Share Common Interview FAQs, Interview Handling Skills & Real-Time Case studies.
- One-to-one Attention by Instructors
- Start learning data science through the promising Julia language and to become an efficient data scientist

What is Data Science?

Data science refers to the study of where information comes from, what it means and how it can be turned into valuable information in the creation of corporate businesses and IT strategies.

Mining large amounts of structured, unstructured and semi-structured data to identify relations can help an organization limit its costs, increase efficiencies, identify new market opportunities and enlarge the organization's competitive advantage.

Today, Data Science is a much-talked subject and moreover, its significance is being deliberated among the business managers who are eager to hire a brilliant professional onboard their firm. Data Science is a growing field and the demand for data scientists has been anticipated to increase this decade in the IT sector.

Key Highlights

Designed for Working Professionals
400+ Hours of Learning
60+ Case Studies and Projects
5 Unique Specialisations
Practical Hands-on Workshops
One-on-One with Industry Mentors
Fortnightly Mentorship with Industry Experts
Job Assistance with Top Firms
No Cost EMI Option

Statistics

1. Fundamentals of Data Science and Machine Learning

Introduction to Data Science
The need for Data Science
BigData and Data Science
Data Science and machine learning
Data Science Life Cycle
Data Science Platform
Data Science Use Cases
Skill Required for Data Science

2. Mathematics For Data Science

Linear Algebra
Vectors
Matrices
Optimization
Theory Of optimization
Gradients Descent

3. Introduction to Statistics

Descriptive vs. Inferential Statistics
Types of data
Measures of central tendency and dispersion
Hypothesis & inferences
Hypothesis Testing
Confidence Interval
Central Limit Theorem

4. Probability and Probability Distributions

Probability Theory
Conditional Probability
Data Distribution
Binomial Distribution
Normal Distribution

Python for Data Science

1. An Introduction to Python

Why Python, its Unique Feature and where to use it?
Python Environment Setup/shell
Installing Anaconda
Understanding the Jupyter notebook
Python Identifiers, Keywords
Discussion about installed modules and packages

2. Conditional Statement, Loops, and File Handling

Python Data Types and Variable
Condition and Loops in Python
Decorators
Python Modules & Packages
Python Files and Directories manipulations
Use various files and directory functions for OS operations

3. Python Core Objects and Functions

Built-in modules (Library Functions)
Numeric and Math’s Module
String/List/Dictionaries/Tuple
Complex Data structures in Python
Python built-in function
Python user-defined functions

4. Introduction to NumPy

Array Operations
Arrays Functions
Array Mathematics
Array Manipulation
Array I/O
Importing Files with Numpy

5. Data Manipulation with Pandas

Data Frames
I/O
Selection in DFs
Retrieving in DFs
Applying Functions
Reshaping the DFs - Pivot
Combining DFs
Merge
Join
Data Alignment

6. SciPy

Matrices Operations
Create matrices
Inverse, Transpose, Trace, Norms, Rank etc
Matrices Decomposition
Eigenvalues & vectors

7. MatPlotLib

Basics of Plotting
Plots Generation
Customization
Store Plots

Machine Learning

1. Exploratory Data Analysis

Data Exploration
Missing Value handling
Outliers Handling
Feature Engineering

2. Feature Selection

Importance of Feature Selection in Machine Learning
Filter Methods
Wrapper Methods
Embedded Methods

3. Machine Learning: Supervised Algorithms Classification

Introduction to Machine Learning
Logistic Regression
Naïve Bays Algorithm
K-Nearest Neighbor Algorithm
Decision Trees (SingleTree)
Support Vector Machines
Model Ensemble
- - Bagging
- - Random Forest
- - Boosting
- -Gradient Boosted Trees
Model Evaluation and performance
- - K-Fold Cross-Validation
- - ROC, AUC, etc...