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Introduction to Data Science, Machine Learning & AI

Become a skilled data scientist in this comprehensive course, where you'll learn the foundational skills and techniques needed to succeed in the fields of data science, machine learning, and AI using Python. From exploring the role of a data scientist to applying machine learning algorithms and building recommendation engines, you'll gain hands-on experience and develop a deep understanding of the data science process. Join us and unlock the potential of data-driven decision-making.

  • Beginner
  • 18 and older
  • $3,190
  • 13650 Dulles Technology Dr, Herndon, VA
  • 37 hours & 30 minutes over 5 sessions

Start Dates (0)

  • $3,190
  • Herndon Education and AnyWare Center @ 13650 Dulles Technology Dr Ste #175, Herndon, VA 20171
  • 37 hours & 30 minutes over 5 sessions
  • Course 1264
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Class Description

Description

What you'll learn in this business intelligence training:

Introduction to Data Science, Machine Learning & AI using Python

Data science is a field that has exploded in popularity in recent years, and for good reason. Companies across industries are increasingly relying on data to inform their decision-making, and skilled data scientists are in high demand. In this comprehensive course, you'll learn the foundational skills and techniques you need to succeed in this exciting field.

You'll start by exploring the role of a data scientist and the lifecycle of data science efforts within an organization. Then, you'll dive into the technical skills you need, such as using Python and its relevant libraries for data analysis and visualization, preprocessing unstructured data, and building AI/ML models.

You'll also explore key machine learning algorithms, including linear regression, decision tree classifiers, and clustering algorithms. And, you'll learn how to apply these techniques to real-world problems, such as predicting customer churn and building recommendation engines.

Throughout the data science training, you'll have the opportunity to work on hands-on exercises and projects, allowing you to practice your skills and build your portfolio. By the end of the course, you'll have a deep understanding of the data science process, the tools and techniques used by data scientists, and the ability to apply these skills to real-world problems.

In this course, you will:

  • Translate everyday business questions and problems into Machine Learning tasks to make data-driven decisions
  • Use Python Pandas, Matplotlib & Seaborn libraries to explore, analyze, and visualize data from various sources including the web, word documents, email, NoSQL stores, databases, and data warehouses
  • Train a Machine Learning Classifier using different algorithmic techniques from the Scikit-Learn library, such as Decision Trees, Logistic Regression, and Neural Networks
  • Re-segment your customer market using K-Means and Hierarchical algorithms for better alignment of products and services to customer needs
  • Discover hidden customer behaviors from Association Rules and build a Recommendation Engine based on behavioral patterns
  • Investigate relationships & flows between people and business-relevant entities using Social Network Analysis
  • Build predictive models of revenue and other numeric variables using Linear Regression
  • Gain access to an exclusive LinkedIn group for peer and community support
  • Test your knowledge with the included end-of-course exam
  • Leverage continued support with after-course one-on-one instructor coaching and computing sandbox

Data Science in Python Instructor-Led Course Outline

  • Module 1: The Role of a Data Scientist: Combining Technical and Non-Technical Skills
  • Module 2: Data Manipulation and Visualization using Python's Pandas and Matplotlib Libraries
  • Module 3: Preprocessing and Analyzing Unstructured Data with Natural Language Processing
  • Module 4: Linear Regression and Feature Engineering for Business Problem Solving
  • Module 5: Classification Models and Evaluation for Predictive Analysis
  • Module 6: Alternative Approaches to Classification and Model Evaluation
  • Module 7: Clustering Techniques for Customer and Product Segmentation
  • Module 8: Association Rules and Recommender Systems for Business Applications
  • Module 9: Network Analysis for Organizational Insights
  • Module 10: Big Data Analytics, Communication, and Ethics

Refund Policy

If a customer would like to cancel or transfer their course, they must notify Coursehorse prior to 3 weeks before the start date of the course or within seven days of registration. On-Demand Courses cannot be cancelled once purchased and are not eligible for refund.

  • If a customer transfers to another course prior to 3 weeks before the start date or within seven days of registration of the course in which originally enrolled, 100% of any prepaid course tuition will be applied toward the course tuition for the subsequent course.
  • If a customer needs to cancel an enrollment 3 weeks prior to the start of the class or within seven days of registration, we will refund 95% of any prepaid course tuition for that enrollment.
  • If a customer does need to transfer or cancel a course within 3 weeks of the start date of the course or after seven days from the date of registration, a fee equal to 50% of the price of the course will be assessed for any standard attendances.

Attendances associated with a Learning Tree program will be assessed a $500 fee. Training Passports, Training Vouchers and Pay-As-You-Learn Vouchers cannot be used after their expiration dates, and a course cancellation or transfer by the customer will not extend a Training Passport, Training Voucher Pack or Pay-As-You-Learn Voucher Pack expiration date.

In the event that an instructor or the school needs to cancel at the last minute, students will receive a refund less a 5% non-refundable registration fee.

In any event where a customer wants to cancel their enrollment and is eligible for a full refund, a 5% processing fee will be deducted from the refund amount.

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  • This class will earn you 31900 points. Points give you money off your next class!

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Learning Tree International

Established in 1974, Learning Tree International is a leading provider of IT training and management training to business and government organizations worldwide. In addition, Learning Tree provides IT Workforce Optimization Solutions – a modern approach that improves the adoption of skills, and accelerates...

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Learning Tree International

Learning Tree International

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