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Curriculum Designed by Experts

Multisoft Virtual Academy’s Data Science with Python Corporate Training is a comprehensive, instructor-led program crafted for organizations aiming to equip their teams with cutting-edge data analysis and machine learning skills. The course covers Python fundamentals, data wrangling, visualization, statistical modeling, and machine learning algorithms. Participants will gain real-world insights through project-based learning and case studies, enabling them to transform raw data into actionable business intelligence. Customized training modules are available to match your organization's goals and skill levels.
This corporate training is ideal for IT professionals, analysts, engineers, and business teams who wish to stay ahead in the data-driven world. Delivered by certified trainers with industry experience, this course ensures measurable ROI through enhanced employee performance and strategic business impact.
The purpose of data science with python training offered by Multisoft Virtual Academy is to insight the candidates on how to Install the required Python environment and other auxiliary tools and libraries, moreover, the aspirants will get hands-on experience on:
Mastering Python and using its packages: The course covers PROC SQL, SAS Macros, and various statistical procedures like PROC UNIVARIATE, PROC MEANS, PROC FREQ, and PROC CORP. You will learn how to use SAS for data exploration and data optimization.
Mastering advanced analytics techniques: The course also covers advanced analytics techniques like clustering, decision tree, and regression. The course covers time series, it's modeling, and implementation using SAS.
Topics
- Introduction to the Data Science
- Different Sectors Using Data Science
- The Purpose and Components of Python

- The Data Analytics Process
- Exploratory the Data Analysis (EDA)
- EDA-Quantitative Technique
- EDA - Graphical Technique
- The Data Analytics Conclusion or Predictions
- The Data Analytics Communication
- The Data Types for Plotting

- Introduction to the Statistics
- About Statistical and Non-statistical Analysis
- The Major Categories of Statistics
- About the Statistical Analysis Considerations
- The Population and Sample
- What is the Statistical Analysis Process?
- The Data Distribution
- Dispersion

- About the Anaconda
- The Installation of Anaconda Python Distribution
- Data Types in the Python
- Basic Operators and Functions

- An Introduction to the Numpy
- The Activity-Sequence it Right
- Class and Attributes of ndarray
- All About the Basic Operations
- Activity-Slice It
- Copy and Views
- About the Mathematical Functions of Numpy

- Introduction to the SciPy
- About the SciPy Sub Package - Integration and Optimization
- What is SciPy sub package?
- Know About the SciPy Sub Package - Statistics, Weave and IO

- Introduction to the Pandas
- Understanding DataFrame
- The Missing Values
- The Data Operations
- About File Read and the Write Support
- What is Pandas Sql Operation?

- NLP: An Overview
- What are NLP Applications?
- About NLP Libraries-Scikit
- The Extraction Considerations
- The Scikit Learn-Model Training and Grid Search

- Introduction to the Data Visualization
- What are Line Properties?
- (x,y) Plot and Subplots
- The Types of Plots

- Web Scraping and Parsing
- Understanding and Searching the Tree
- Know the Navigating options
- Know About Modifying the Tree
- How to Parse and Print the Document?

- Know Why Big Data Solutions are provided for Python?
- Describing Hadoop Core Components
- The Python Integration with HDFS using Hadoop Streaming
- The Python Integration with Spark using PySpark

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Customized trainings to understand specific project requirements
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Free Data Science with Python Corporate Training Assessment
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Data Science with Python Corporate Training Certification
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