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Data Science with Python Training

Live Online & Classroom Enterprise Training

Teaches Python fundamentals for data cleaning, visualization, and predictive analytics. Covers libraries like Pandas, NumPy, Matplotlib, and Scikit-learn.

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What is Data Science with Python Training about?

This course introduces learners to the fundamentals of data science using Python, covering essential libraries, data manipulation, visualization, and machine learning basics. Participants will gain hands-on experience working with real datasets, applying analytical techniques, and building predictive models. The training is designed to bridge theory and practice, equipping learners with practical skills for data-driven decision-making.

What are the objectives of Data Science with Python Training ?

  • Understand Python basics for data science. 
  • Work with key Python libraries (NumPy, Pandas, Matplotlib, Seaborn). 
  • Perform data cleaning, transformation, and analysis. 
  • Visualize insights using charts and graphs. 
  • Build and evaluate simple machine learning models.

Who is Data Science with Python Training for?

  • Beginners aspiring to enter data science. 
  • Students and graduates pursuing analytics careers. 
  • Business Analysts wanting to upgrade to Python. 
  • IT professionals transitioning into data roles. 
  • Professionals interested in machine learning applications.

What are the prerequisites for Data Science with Python Training?

Prerequisites:  
  • Basic programming knowledge (any language preferred). 
  • Understanding of high school-level math & statistics. 
  • Familiarity with data formats (CSV, Excel). 
  • Problem-solving and analytical skills. 
  • Interest in coding and data analysis. 
Learning Path: 
  • Introduction to Python for data science. 
  • Data manipulation with NumPy and Pandas. 
  • Data visualization with Matplotlib and Seaborn. 
  • Data cleaning, preparation, and exploratory analysis. 
  • Introduction to machine learning with Scikit-learn. 
Related Courses: 
  • Introduction to Machine Learning with Python 
  • Data Visualization with Tableau & Power BI 
  • SQL for Data Science 
  • Advanced Python for Analytics

Available Training Modes

Live Online Training

5 Days

Self-Paced Training

8 Hours

Course Outline Expand All

Expand All

  • Introduction to Data Science
  • Python For Data Science
  • Basics of Python
  • Variables with Examples
  • Operators and Its Types
  • Control and Loop Statements
  • Functions and Its Types
  • OOPs Concepts
  • Types of Error and Exception Handling
  • Packages in Python
  • Numpy
  • Data Type in Numpy
  • Indexing and Slicing
  • Mathematical Function
  • Array Manipulation
  • Statistical Functions
  • Concept of Pandas
  • Dataframes
  • Data Manipulations Steps
  • Sorting
  • Filtering
  • Python Built-in Functions
  • Data Visualization
  • Matplotlib
  • Matplotlib
  • Scatter Plot
  • Heat Map
  • Box Plot
  • Pie Chart
  • Descriptive Statistics
  • Descriptive Statistics
  • Probability Distribution
  • Normal Distribution
  • Central Limit Theorem
  • Central Limit Theorem
  • Sampling
  • Z-Test and T-Test
  • ANOVA
  • Chi – Square Test
  • Analytics and Predictive Modelling
  • Import Pandas as PD
  • Exploring Data for Modelling
  • Missing Data
  • Outliers
  • Basics of Regression
  • Types of Regression
  • Multiple Linear Regression
  • Polynomial Regression
  • Cost Function and Gradient Descent
  • Basics of Classification
  • Decision Tree Learning
  • logistic Regression
  • Performing Logistic Regression
  • Support Vector Machines
  • K Nearest Neighbors
  • Native Bayes
  • Ensemble Learning
  • Clustering and Its Applications
  • Hierarchical Clustering
  • Clustering
  • K-Means Clustering
  • K-Means Clustering
  • Introduction to Web Scraping
  • Web Scraping
  • Parser

Who is the instructor for this training?

The trainer for this Data Science with Python Training has extensive experience in this domain, including years of experience training & mentoring professionals.

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