Instructor-led Data Science and Machine Learning Certification live Online Training Schedule

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40,000.00
Duration: 50 Hours

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About your Data Science and Machine Learning Certification Training

Skills Covered

Tools Covered

Data Science and Machine Learning Certification Training Syllabus

Curriculum Designed by Experts

Topics
  • Overview of Data Science
  • Data Science Workflow
  • Setting up the Python environment
Topics
  • Python basics for data science
  • Data types and structures
  • Control flow and functions
  • Working with libraries (NumPy, Pandas)
Topics
  • Introduction to Pandas
  • DataFrames and Series
  • Data cleaning and preprocessing
  • Data transformation and aggregation
Topics
  • Introduction to data visualization
  • Matplotlib and Seaborn basics
  • Creating various types of plots
  • Customizing plots and visualizations
Topics
  • Importance of EDA
  • Techniques for EDA
  • Identifying patterns and relationships
  • Using visualization for EDA
Topics
  • Descriptive statistics
  • Probability theory
  • Inferential statistics
  • Hypothesis testing
Topics
  • Overview of machine learning
  • Supervised vs. unsupervised learning
  • Common machine learning algorithms
  • Evaluation metrics
Topics
  • Linear Regression
  • Logistic Regression
  • Decision Trees and Random Forests
  • Support Vector Machines
  • K-Nearest Neighbors
Topics
  • K-Means Clustering
  • Hierarchical Clustering
  • Principal Component Analysis (PCA)
  • Association Rule Mining
Topics
  • Ensemble methods
  • Gradient Boosting (XGBoost, LightGBM)
  • Neural networks and deep learning basics
  • Natural Language Processing (NLP)
  • Time Series Analysis
Topics
  • Train-test split and cross-validation
  • Model evaluation metrics
  • Hyperparameter tuning
  • Model selection and validation
Topics
  • End-to-End Data Science Project
  • Industry-Specific Projects
  • Best Practices in Data Science and Machine Learning

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Why Data Science and Machine Learning Certification Training From Xpertised Learning

Live Interactive Classes

  • Top-Tier Trainers
  • Real Time Guidance by Industrial Experts
  • In Class Doubt Clearance

Resource Access

  • Life Time Access to Resource Library

Support

  • One-to-One Lab and Training Assistance
  • Help Desk Support
  • Doubt Clearance in Real-time

Project Based Learning

  • Labs and Learning Based from Industrial Experts
  • Learning Based on Project Scenarios

Certification

  • Xpertised Learning Training Certificate
  • Certificate of Completion

Labs

  • Cloud based Labs *Labs based on course requirement only

Data Science and Machine Learning Certification Training Details

This course aims to equip learners with the ability to analyze complex data sets, create data visualizations, and build predictive models using machine learning algorithms. It combines theoretical knowledge with hands-on exercises and real-world projects to ensure that learners can apply their skills in professional settings.

  • Develop expertise in data science and machine learning, enhancing your ability to analyze data and build predictive models.
  • Boost your career prospects by obtaining a certification that is highly valued in the data science and analytics industry, making you a sought-after candidate for data scientist roles.
  • Stay competitive in the job market by mastering data science and machine learning techniques, ensuring your skills remain relevant and in high demand.
  • Hands-on experience with Python and data science libraries.
  • Practical knowledge applicable to real-world scenarios.
  • Enhanced career opportunities in data science, machine learning, and AI.
  • Certification that validates your data science and machine learning skills and knowledge.
  • Python programming for data science
  • Data manipulation and cleaning with Pandas
  • Data visualization with Matplotlib and Seaborn
  • Exploratory Data Analysis (EDA)
  • Statistical analysis
  • Machine learning algorithms and techniques
  • Model evaluation and tuning
  • Time series analysis and NLP
  • Python
  • Jupyter Notebook
  • NumPy
  • Pandas
  • Matplotlib
  • Seaborn
  • Scikit-Learn
  • TensorFlow/Keras (for deep learning)
  • XGBoost, LightGBM
  • Understand the core concepts of data science and Python programming.
  • Perform data manipulation, cleaning, and transformation using Pandas.
  • Create data visualizations to communicate insights effectively.
  • Implement machine learning algorithms and build predictive models.
  • Evaluate and tune machine learning models for better performance.
  • Apply data science and machine learning techniques to real-world projects.
  • Aspiring Data Scientists
  • Data Analysts and Scientists
  • Machine Learning Engineers
  • IT Professionals
  • Anyone interested in data science, machine learning, and AI
  • Basic knowledge of programming concepts is beneficial
  • Familiarity with Python is recommended but not mandatory
  • Core concepts of data science and Python programming
  • Data manipulation, cleaning, and transformation using Pandas
  • Creating data visualizations with Matplotlib and Seaborn
  • Performing exploratory data analysis (EDA)
  • Implementing machine learning algorithms and building predictive models
  • Evaluating and tuning machine learning models
  • Applying data science and machine learning techniques to real-world projects
  • A computer with at least 8GB RAM and 20GB free disk space
  • Stable internet connection
  • Python installed (Python 3.x version)
  • Integrated Development Environment (IDE) like Jupyter Notebook
  • Enhanced job prospects in data science, machine learning, and AI
  • Opportunities to work with top companies leveraging data science and machine learning for their business needs
  • Potential for career growth and higher salaries in roles such as Data Scientist, Data Analyst, and Machine Learning Engineer

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