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Data science with Python is a popular and powerful combination for analyzing, visualizing, and interpreting complex data.

Data Science with AI Training Courses

The Data Science with Python course provides a comprehensive overview of Python’s tools and techniques for data analytics. Learning Python is a vital skill for numerous data science roles, and you can cultivate it through this course.

Course Content

Python Introduction
Installation
First command
Variables
Types of variables
Built in function
List
Dictionary
Tuple
Accessing list items
Accessing list slices
Accessing items and
slices with negative index
Accessing characters and slices in strings
Accessing items in dictionaries
Creating own function
Print vs return
Introduction to conditionals
If condition
Isinstance
Elif conditionals
White space.
User Input
String Formatting
String Formatting with Multiple Variables
For Loops
While Loops
While With Break And Continue
Simple List Comprehension
List Comprehension With If Conditions
List Comprehension With If-Else Conditions
Functions With Multiple ArgumentsDefault & Non-Default Parameter and
Keyword and Non-Keyword Arguments
Functions With an Arbitary Number Of Non-Keyword

File Processing
Reading Text From a File
File Cursor
Closing File
Opening Files Using With
Diffetrent FilePath
Writing A text To File
Appending Text To File
Appending Text To an Existing File
Class And Object
Inheritance
Numpy Introduction
Numpy Array
Numpy Selection & Indexing
Numpy Operations
Pandas Introduction
Series
Dataframes
Dataframes Join, Merge, Concatenation
Dataframes Indexing
Dataframes Multi-index & index Hierarchy
Dataframes GroupBy
Dataframes Data
Input & Output
Regresssion
Linear-Regression
Logistic-Regression
K-Nearest-Neighbors
Decision-Trees-and-Random-Forests
Support-Vector-Machines
K-Means-Clustering
Principal-Component-Analysis
Recommender-Systems
Natural-Language-Processing
Deep Learning
Neural Networks

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Data Science with AI Course Overview

The Data Science with Python course empowers you to excel in Python programming. In this course, you’ll delve into data science, data analysis, data visualization, data wrangling, feature engineering, and statistics. Upon finishing the course, you’ll excel in using essential data science tools with Python.

Data Science with Python Training Key Features

68 hours of blended learning
40+ Assisted practices and lesson-wise knowledge checks
Dedicated live sessions by faculty of industry experts
Curriculum aligned with PL-300: Microsoft Power BI Data Analyst certification
Lifetime access to self-paced learning content
Industry-recognized course completion certificate

Data wrangling
Web scraping
ScikitLearn package for Natural Language Processing
Hypothesis building
Python programming concepts
Data exploration
Data Visualization
NumPy and SciPy package

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Explore Training Program

In Group

Learners can share insights, ask questions, and engage in discussions, fostering a collaborative learning atmosphere.
Courses are typically designed with a set curriculum that aims to meet the learning objectives of the group as a whole.
Training sessions are scheduled at predetermined times, which can help learners maintain a consistent learning routine.

One on One

The trainer focuses solely on one student, allowing for immediate feedback, personalized guidance, and a learning pace that suits the individual.
One-on-one training often comes with the flexibility to schedule sessions at times that are most convenient for the learner, accommodating their personal and professional commitments.

Weekend Batch

Classes are usually held on weekends, making it convenient for those who are busy during the weekdays.
Since the classes are on weekends, the training sessions might be longer than typical weekday classes, aiming to cover the syllabus efficiently over a shorter period.