Data Science Course & Training | Online with Python Certification

Grow Your Career with Data Science

Aspirants need to go through interactive exercises, obtain hands-on with the most popular Python libraries, incorporating NumPy, pandas, Matplotlib, etc. the training assist you in work-on on real-world datasets. This enables participants to study the arithmetical and machine learning processes to know about the decision trees and apply natural language processing (NLP).

Begin the learning process, enhance your Python skills, and start the venture to turn out a convinced data scientist.

Data Science is a scientific method that helps in learning a variety of data patterns delivered by users. The scientific methodology applies technologies such as Python and R to understand the data.

Python for data scientist

Master the fundamentals of data analysis in Python. Develop your ability set by learning scientific computing.

Usually, data science is a structural design that uses scientific computing, algorithm, framework, and haul out the insight knowledge base. The data scientists study the data received in structured or unstructured data format. After scrutinizing the data, the scientists deliver implausible solutions to the corporations so that establishments could take accurate data-driven decisions.

Python is general-reason programming that is turning out to be more recognized for data science. Globally, businesses are applying Python to crop insights from their data and increase a competitive edge. However, differentiating wifromormer Python tutorials, the data science with Python course aims at Python purposely for data science.

In the Python course, candidates will study the most useful paths to store and influence data, and require data science tools to start conducting their own anes.

Begin the journey in data science with Python training by enrolling at Mildain Solutions.

Advantages of Data Science

You learn to take the right decision depending on data analysis
Python with data science enhance the capabilities of decision making
Errors and latencies are curved smartly
Assist enterprises in improving the relationship with their customers
Data Science is the key to growing businesses

Additionally, the raw features of copious packages present advanced graphical competencies. The technology Python is used for preparing tailored-made graphs in the programming language.

Why advise Python with Data Science?

Participants registering in data science with a Python course will recognize that Python is a swift, chronological, and open-source programming language. This is not difficult to apply. One of the chief inspiring keys of using code in data analysis is that it reindeer collaborations (collabs). Candidates in training certification learn to replicate it. It incorporates counts, submissions, or identifies mistakes in scrutiny.

How data science with Python certification is achieving its way.

Carrying out the training in data science enables candidates to discover quick jobs, a better data community, and a high salary. Python delivers a faster presentation, has skilled features, constituent better essential features compared to big data solutions, web frameworks, and unit testing.

The industry is searching for participants who can examine data interacting with Python tools. This incorporates store data.

How Python is recognizing industries.

Data science being an obtainable category in analyzing data, Python in data science permits data scientists to interrelate with Python tools to examine and store data.

Top 10 reasons t0 use Python in Data Science:

Python is an active, free open source, high-level, and interpreted programming language. It renders the programming method of object-oriented and procedural-oriented programming.

Python is a dynamic language that does not require stating the uneven type.
The language that supports object-orientation - One of the essential features of python is Object-Oriented programming. Python renders concepts of objects encapsulation, and classes, etc.
Graphical User Interface Programming Support - Graphical User interfaces are developed using a module like PyQt4, PyQt5, wxPython, and Tk.
Efficient coding - Python is easy to learn as compared to other languages such as C, C#, JavaScript, Java, etc. It is an efficient high-level programming language, which requires just a few hours for the students to learn to code
Accessible to all - Python language is an open-source high-level language that can be downloaded and accessed without paying a cent. Aspirants can access its source code.
Portable language - Python is a portable language. For instance, if you have developed a code for Mac, the code will run on Linux and UNIX as well.
Language – High level - Python is a flexible language that allows developers to avoid remembering the system architecture or managing the memory.
Extensible feature - Python is an extensible language that allows developers to write Python code in the C/C++ language.
Interpreted Language - Python can easily be integrated with other languages like C, C++, etc.
Large Standard Library - Python delivers a rich set of purposes and modules to write your code.

There are several libraries available in python for such as usual expressions, web browsers, and unit testing.

What you will Learn

The Data Science with Python course will give you in-depth knowledge of the various libraries and packages required to perform data analysis, data visualization, web scraping, machine learning and natural language processing using Python. With this Data Science with Python course, you will learn to work with Python packages such as PROC SQL and various statistical procedures such as PROC UNIVARIATE, PROC MEANS, PROC FREQ, and PROC CORP, as well as advanced analytics techniques such as clustering, decision tree, and regression.
The Python for Data Science course is packed with real-life projects focused on customer segmentation, macro calls, attrition analysis, and retail analysis, as well as demos and case studies to give you practical experience in installing and working in the Python environment.
Python has surpassed Java as the top language used to introduce US students to programming and computer science, and 46 percent of data science jobs list Python as a required skill.

PREREQUISITES

Prerequisites: There are no prerequisites for this Data Science with Python course. The Python basics course included with this program provides additional coding guidance.

CURRICULUM

Learning Objectives:

Course Overview
Data Science Overview

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

Learning Objectives:

Data Analytics Process
Knowledge Check
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

Learning Objectives:

Introduction to Statistics
Statistical and Non-statistical Analysis
Major Categories of Statistics
Statistical Analysis Considerations
Population and Sample
Statistical Analysis Process
Data Distribution
Dispersion
Histogram
Testing
Correlation and Inferential Statistics

Learning Objectives:

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

Learning Objectives:

Introduction to Numpy
Activity-Sequence it Right
Creating and Printing an ndarray
Knowledge Check
Class and Attributes of ndarray
Basic Operations
Activity-Slice It
Copy and Views
Mathematical Functions of Numpy

Learning Objectives:

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

Learning Objectives:

Introduction to Pandas
Understanding DataFrame
View and Select Data Demo
Missing Values
Data Operations
Knowledge Check
File Read and Write SupportPreview
Knowledge Check-Sequence it Right
Pandas Sql Operation

Learning Objectives:

Machine Learning Approach
How it Works
Supervised Learning Model Considerations
Scikit-Learn
Supervised Learning Models – Linear Regression
Supervised Learning Models – Logistic Regression
Unsupervised Learning Models
Pipeline
Model Persistence and Evaluation

Learning Objectives:

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

Learning Objectives:

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

Learning Objectives:

Web Scraping and Parsing
Knowledge Check
Understanding and Searching the Tree
Navigating options
Navigating a Tree
Modifying the Tree
Parsing and Printing the Document

Learning Objectives:

Why Big Data Solutions are Provided for Python
Hadoop Core Components
Python Integration with HDFS using Hadoop Streaming
Python Integration with Spark using PySpark

FAQs

You can enroll for this classroom training online. Payments can be made using any of the following options and receipt of the same will be issued to the candidate automatically via email.
1. Online ,By deposit the mildain bank account
2. Pay by cash team training center location

Highly qualified and certified instructors with 20+ years of experience deliver more than 200+ classroom training.

Contact us using the form on the right of any page on the mildaintrainings website, or select the Live Chat link. Our customer service representatives will be able to give you more details.

You will never miss a lecture at Mildaintrainigs! You can choose either of the two options: View the recorded session of the class available in your LMS. You can attend the missed session, in any other live batch.

We have a limited number of participants in a live session to maintain the Quality Standards. So, unfortunately, participation in a live class without enrollment is not possible. However, you can go through the sample class recording and it would give you a clear insight about how are the classes conducted, quality of instructors and the level of interaction in a class.

Yes, you can cancel your enrollment if necessary prior to 3rd session i.e first two sessions will be for your evaluation. We will refund the full amount without deducting any fee for more details check our Refund Policy

Yes, the access to the course material will be available for lifetime once you have enrolled into the course.

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