Instructor-led AI and Machine Learning in Finance live Online Training Schedule

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Price:
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35,000.00
Duration: 50 Hours

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About your AI and Machine Learning in Finance Training

Skills Covered

Tools Covered

AI and Machine Learning in Finance Training Syllabus

Curriculum Designed by Experts

Topics
  • Basics of AI and Machine Learning
  • Overview of AI and ML in Finance
  • Key Concepts and Terminology
Topics
  • Data Cleaning and Preparation
  • Exploratory Data Analysis
  • Feature Engineering
Topics
  • Linear and Logistic Regression
  • Decision Trees and Random Forests
  • Support Vector Machines
  • Neural Networks
Topics
  • Clustering Techniques
  • Principal Component Analysis
  • Anomaly Detection
Topics
  • Introduction to Time Series Data
  • ARIMA Models
  • LSTM Networks for Time Series Prediction
Topics
  • Sentiment Analysis
  • Text Mining and Analysis
  • Applications in Financial News and Reports
Topics
  • Algorithmic Trading Strategies
  • Backtesting and Optimization
  • Risk Management in Trading
Topics
  • Credit Risk Modeling
  • Fraud Detection
  • Stress Testing and Scenario Analysis
Topics
  • Ethics in AI and Machine Learning
  • Regulatory Compliance in Finance
  • Data Privacy and Security

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Why AI and Machine Learning in Finance 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

AI and Machine Learning in Finance Training Details

This course provides a comprehensive understanding of AI and machine learning concepts, focusing on their application in finance. Participants will learn how to use AI and ML to analyze financial data, predict market trends, automate trading strategies, and manage financial risks.

  • Gain specialized knowledge in applying AI and machine learning techniques to financial markets, a rapidly growing area with high demand for skilled professionals.
  • Enhance your career prospects by acquiring cutting-edge skills that are highly valued in the finance industry, opening up opportunities in investment banking, risk management, and fintech.
  • Stay ahead of industry trends and developments, positioning yourself as a forward-thinking professional capable of driving innovation in financial services.
  • Develop advanced analytical skills.
  • Improve decision-making capabilities using AI and ML.
  • Stay ahead in the competitive finance industry.
  • Practical, hands-on experience with real-world financial data.
  • Data preprocessing and analysis
  • Supervised and unsupervised learning techniques
  • Time series analysis
  • Natural language processing
  • Algorithmic trading strategies
  • Risk management
  • Python and R programming languages
  • Machine learning libraries (scikit-learn, TensorFlow, Keras)
  • Financial data analysis tools (Pandas, NumPy)
  • Visualization tools (Matplotlib, Seaborn)
  • Understand the fundamentals of AI and machine learning.
  • Apply AI and ML techniques to financial data.
  • Develop and implement trading algorithms.
  • Use AI and ML for risk management and decision-making.
  • Finance professionals
  • Data scientists
  • Quantitative analysts
  • Risk managers
  • Anyone interested in AI and ML applications in finance
  • Basic knowledge of programming (Python or R)
  • Understanding of finance and financial markets
  • Fundamental concepts of AI and machine learning.
  • Practical applications of AI and ML in finance.
  • Developing and implementing AI and ML models.
  • Analyzing and interpreting financial data using AI and ML techniques.
  • A computer with an internet connection
  • Python or R installed
  • IDEs like Jupyter Notebook or RStudio
  • Data Scientist in Finance
  • Quantitative Analyst
  • Financial Analyst
  • Risk Manager
  • Algorithmic Trader

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