Python for Data Science online training, you will gain knowledge in data analysis, machine learning, data visualization, web scraping, & natural language processing.
To perform scientific and technical computing using SciPy package and its sub-packages such as Integrate, Optimize, Stat...
Perform data analysis and manipulation using data structures and tools provided in Pandas package
Gain an in-depth understanding of supervised learning and unsupervised
learning models like linear regression, logistic regression, clustering, dimensionality reduction, K-NN, and pipeline. U...
How to use the matplotlib library of Python for data visualization. Extract useful data from websites by performing web...
Integrate Python with Hadoop, Spark, and MapReduce
Requirements
There are no prerequisites for this course. The Python basics course included with this course provides an additional coding guidance.
Description
|| About Python for Data Science Training Course
This interactive and comprehensive course is a great place for you to get started on Python programming language and its use in Data Science.This Python for Data Science online training course from BIT aims at helping you understand the core concepts of Data science including exploratory data science, statistics, hypothesis testing, regression classification modeling techniques, data visualization and machine learning algorithms. The Data Science with Python course has been designed to provide in-depth knowledge of the various libraries and packages that are required to perform data analysis, data visualization, web scraping, machine learning, and natural language processing using Python. Data Science with Python course enables you to master Data Science Analytics using Python. You will work on various python libraries like SciPy, NumPy, Matplotlib, Lambda function, etc. You will master data science analytics skills through real-world projects in multiple domains like Retail, e-commerce, Finance, etc.
This Python for Data Science training is beneficial for analytics professionals willing to work with Python, Software, and IT professionals interested in the field of analytics, and anyone with a genuine interest in Data Science. Python Data Science courses including, Introduction to Data Science in Python, Math Refresher, Data Science in Real Life, and Statistics Essentials for Data Science. These courses are offered as free companions with this program.
Course Content
Live Lecture
·Introduction to Python Language
·Features, the advantages of Python over other programming languages
·Python installation – Windows, Mac & Linux distribution for Anaconda Python
·Deploying Python IDE
·Basic Python commands
·Data types
·Variables
·Keywords and more
·Practical Exercise
Live Lecture
·The Companies using Python
·Different Applications where Python is used
·Discuss Python Scripts on UNIX/Windows
·Values, Types, Variables
·Operands and Expressions
·Conditional Statements
·Loops
·Command Line Arguments
·Writing to the screen
·Practical Exercise
Live Lecture
·Python files I/O Functions
·Numbers
·Strings and related operations
·Tuples and related operations
·Lists and related operations
·Dictionaries and related operations
·Sets and related operations
·Practical Exercise
Live Lecture
·Functions
·Function Parameters
·Global Variables
·Variable Scope and Returning Values
·Lambda Functions
·Object-Oriented Concepts
·Standard Libraries
·Modules Used in Python
·The Import Statements
·Module Search Path
·Package Installation Ways
·Errors and Exception Handling
·Handling Multiple Exceptions
·Practical Exercise
Live Lecture
·Understanding the Database, need of database
·Installing MySQL on windows
·Understanding Database connection using Python.
·Practical Exercise
Live Lecture
·Introduction to arrays and matrices
·Broadcasting of array math, indexing of array
·Standard deviation, conditional probability, correlation and covariance.
·Reading and writing arrays on files
·How to import NumPy module
·Creating array using ND-array
·Calculating standard deviation on array of numbers
·Calculating correlation between two variables.
·Practical Exercise
Live Lecture
·Introduction to SciPy
·Functions building on top of NumPy
·Cluster, linalg, signal, optimize, integrate
·Subpackages, SciPy with Bayes Theorem.
·Importing of SciPy
·Applying the Bayes theorem on the given dataset.
·Practical Exercise
Live Lecture
·How to plot graph and chart with Python
·Various aspects of line, scatter, bar, histogram, 3D
·The API of MatPlotLib
·Subplots
·Practical Exercise
Live Lecture
·Introduction to Python dataframes
·Importing data from JSON, CSV, Excel, SQL database,
·NumPy array to dataframe
·Various data operations like selecting
·Filtering, sorting, viewing, joining, combining
·Working on importing data from JSON files
·Selecting record by a group
·Applying filter on top, Viewing records
·Practical Exercise
Live Lecture
·Introduction to Exception Handling
·Scenarios in Exception Handling with its execution
·Arithmetic exception
·RAISE of Exception
·What is Random List
·Running a Random list on Jupyter Notebook
·Value Error in Exception Handling.
·Practical Exercise
Live Lecture
·Introduction to Thread, need of threads
·What are thread functions
·Performing various operations
·Joining a thread
·Starting a thread
·Enumeration in a thread
·Creating a Multithread
·Finishing the multithreads
·Understanding Race Condition
·Lock and Synchronization
·Practical Exercise
Live Lecture
·Intro to modules in Python, need of modules
·How to import modules in python
·Locating a module, namespace and scoping
·Arithmetic operations on Modules using a function
·Intro to Search path,
·Global and local functions
·Filter functions
·Python Packages
·Import in packages
·Various ways of accessing the packages
·Decorators
·Pointer assignments, and Xldr
·Practical Exercise
Live Lecture
·Introduction to web scraping in Python
·Installing of beautifulsoup
·Installing Python parser lxml
·Various web scraping libraries
·Beautifulsoup,
·Scrapy Python packages
·Creating soup object with input HTML
·Searching of tree, full or partial parsing, output print
·Practical Exercise
Case Studies
Fees
Offline Training @ Vadodara
Classroom Based Training
Practical Based Training
No Cost EMI Option
4500040000
Online Training preferred
Live Virtual Classroom Training
1:1 Doubt Resolution Sessions
Recorded Live Lectures*
Flexible Schedule
4000035000
Corporate Training
Customized Learning
Onsite Based Corporate Training
Online Corporate Training
Certified Corporate Training
Certification
Upon the completion of the Classroom training, you will have an Offline exam that will help you prepare for the Professional certification exam and score top marks. The BIT Certification is awarded upon successfully completing an offline exam after reviewed by experts
Upon the completion of the training, you will have an online exam that will help you prepare for the Professional certification exam and score top marks. BIT Certification is awarded upon successfully completing an online exam after reviewed by experts.
