metamorfeus

Signup Today
Business with Artificial Intelligence and Automation course

Business with Artificial Intelligence and Automation

Are you ready to revolutionize your business strategy and stay ahead of the curve in the age of AI? This isn’t just another tech course; it’s your gateway to becoming a data-driven, AI-powered leader in your niche. Here’s what you’ll master: Become an AI Strategist: Go beyond the buzzwords and understand exactly how AI can be applied…

$4,500.00
Category:

Description

Course Objective: To provide participants with an understanding of the capabilities of artificial intelligence (AI) and automation in business, with a focus on practical applications and the use of Python for business process automation.

Target Audience: Business professionals, managers, financial specialists, marketing specialists, project management specialists, and anyone interested in applying AI and automation in business.

Course Modules:

Module 1: Introduction to the 4th Industrial Revolution and Artificial Intelligence in Business
* 4th Industrial Revolution: Overview and key characteristics.
* Business in the Industry 4.0 era: Challenges and opportunities.
* What is Artificial Intelligence (AI)? The simplest explanation.
* What do companies expect from AI? (According to Forrester data)
* Benefits of automation and AI for business:
* Improving efficiency and productivity.
* Reducing errors and optimizing processes.
* More accurate information for decision-making.
* Releasing human resources for creative tasks.
* Examples of successful automation in business (Microsoft Finance Department).
* Providers of AI platforms and services (OpenAI, Anthropic, Hugging Face, Google, Perplexity, Nvidia, Meta).

Module 2: Introduction to Business Process Automation with Python
* What is Python and why is it suitable for automation?
* Examples of Python applications in business process automation.
* Key Python libraries for automation and data analysis (Pandas, NumPy, ReportLab, Prophet, statsmodels, Keras, TensorFlow, Dash, Streamlit).
* Tools for developing and deploying automation (Docker, Kubernetes).
* Automation architecture: Microservices and communication between them.
* Security in process automation: Monitoring and logging.

Module 3: Practical Applications of AI in Project Management
* Situational analysis: Managing a project to implement CRM automation with AI (Example: Metamorfeus and Trek Bikes).
* Using Google AI Studio for project management.
* Tasks in managing projects with AI:
* Creating documentation and specifications with AI.
* Project planning with AI.
* Collaboration and communication with clients using AI.
* Personalization of systems with AI.
* Brainstorming and planning with AI.
* Answering client questions about AI implementation:
* Selection of AI models for customer segmentation, churn prediction, and personalized recommendations.
* Project timeline, key milestones, and deliverables.
* Engaging the client team in testing and training.
* Project budget and breakdown by item.
* Creating prompts for AI for project management (Examples from the presentation).

Module 4: AI for Analysis and Comparison of Contractual Relationships
* Situational analysis: Comparison of supplier agreements (Example: MASTERCO Traders).
* Using AI to compare contracts and generate reports.
* Creating a report comparing supplier agreements.
* Generating recommendations for renewing contracts with more favorable terms.
* Practical exercises for analyzing contracts with AI.

Module 5: Data Analysis and Financial Report Generation with AI
* Analysis of marketing campaigns with AI:
* Calculating ROI, CPA, and other key metrics.
* Identifying the most effective campaigns.
* Practical exercises with marketing campaign data (Fairbanks).
* Generating financial reports with AI:
* Creating reports on financial results.
* Analyzing financial data and identifying trends (Example: Dow Chemical).
* Suggesting ideas for further data analysis with AI.
* Summarizing financial data and evaluating financial performance with AI.

Module 6: Data Consolidation and Cleaning with Python
* Problems with consolidating data from multiple sources (different formats, column names, missing data).
* Automation of data consolidation with Python.
* Writing Python scripts for:
* Finding and processing files in various formats (.xlsx, .csv, .txt).
* Cleaning and standardizing data (column names, data formats, missing values).
* Consolidating data from multiple sources into a single file.
* Logging and error handling in Python scripts.
* Examples of data cleaning and unification (capitalization, data types, range validation, email validation, dates, duplicates).

Module 7: Automation of Financial Processes with Python
* Automation of reporting for standards and regulatory requirements with Python.
* Budgeting and forecasting with Python:
* Using Python to forecast future revenues and expenses.
* Using libraries for time series forecasting (Prophet, ARIMA).
* Consolidation of financial statements with Python for organizations with subsidiaries.
* Predictive financial modeling and scenario analysis with Python.
* Generating personalized financial dashboards with Python (Dash, Streamlit).
* Automation of tax calculations with Python.

Module 8: Agent Workflows and Personal Assistants with AI
* Concept of agent workflows and their application in business.
* Creating personal assistants with AI to automate routine tasks.
* Analyzing personal writing style with AI and adapting communication tone.
* Creating an AI assistant for writing emails with a specific tone and style.

Module 9: Business Process Transformation and the Future of Automation
* Transition from automating individual tasks to transforming entire business processes.
* How to transform 1000 processes per year?
* Strategic approach to automation and AI implementation in the organization.
* Ethical aspects of using AI and automation in business.
* Future of work in the age of AI and automation (forecasts by McKinsey and Goldman Sachs).

Related products