Currently, ML Skills Academy offers a single, comprehensive course: 12-Week Machine Learning for Beginners. This course is designed to provide a solid foundation in machine learning for those who are new to the field.

Over 12 weeks, you’ll learn key concepts such as data preprocessing, basic algorithms, model evaluation, and more. The course includes hands-on projects and practical exercises to ensure you gain real-world experience and confidence in applying machine learning techniques.

This course is designed for anyone who is new to machine learning, regardless of their background. Whether you’re a complete beginner, a tech professional looking to upskill, or a career changer interested in entering the field of machine learning, this course provides the essential knowledge and practical experience you need to get started. No prior programming or data science experience is required, as the course begins with the fundamentals and gradually builds up to more complex concepts.

By the end of the 12-Week Machine Learning for Beginners course, you will have a solid understanding of key machine learning concepts and techniques. You’ll be able to:

• Understand the basics of machine learning and its applications.
• Work with datasets, including data preprocessing and cleaning.
• Build and evaluate machine learning models using algorithms such as linear regression, decision trees, and clustering.
• Implement models using Python and popular ML libraries like Scikit-learn.
• Apply machine learning to solve practical problems through hands-on projects.

You’ll also complete a capstone project, which will allow you to apply what you’ve learned to a real-world scenario, giving you a portfolio-ready piece of work to showcase to potential employers.

The 12-Week Machine Learning for Beginners course is structured to provide a balanced mix of theory and practice, ensuring you build a strong foundation in machine learning while gaining hands-on experience. Here’s how the course is organized:

• Weekly Modules: Each week focuses on a specific aspect of machine learning, starting with the basics and gradually moving to more advanced topics. Modules include video lectures, readings, and coding exercises.

• Hands-On Projects: Throughout the course, you’ll work on practical projects that reinforce the concepts learned. These projects are designed to simulate real-world scenarios, helping you apply your skills in meaningful ways.

• Capstone Project: In the final weeks, you’ll undertake a capstone project that integrates everything you’ve learned. This project will challenge you to solve a real-world problem using machine learning, resulting in a tangible output you can showcase.

• Support and Feedback: You’ll have access to a community of learners, as well as support from instructors and teaching assistants. Regular feedback on your projects and assignments ensures you stay on track and continuously improve.

• Self-Paced Learning: While the course is designed to be completed in 12 weeks, you can learn at your own pace, allowing flexibility to balance your studies with other commitments.

The 12-Week Machine Learning for Beginners course is designed to be accessible to everyone, so there are no formal prerequisites. However, having a basic understanding of high school-level mathematics, such as algebra and statistics, will be helpful. The course also introduces programming in Python, but no prior coding experience is required, as we start from the basics and provide guidance throughout. All necessary tools and software will be introduced and explained during the course, so you can confidently build your skills from the ground up.

Yes, ML Skills Academy offers the option to pay for the 12-Week Machine Learning for Beginners course in installments. We understand that spreading out the cost can make it more manageable, so you can choose to break the payment into multiple installments during the checkout process. Detailed information on the available installment plans will be provided when you enroll, and you can select the option that best suits your financial situation. If you have any questions or need assistance with the payment process, our support team is here to help.

Yes, upon successfully completing the 12-Week Machine Learning for Beginners course, you will receive a Certificate of Completion from ML Skills Academy. This certificate verifies that you have acquired foundational machine learning skills and completed the required projects. It can be added to your resume or LinkedIn profile to showcase your newly gained expertise to potential employers. The certificate is a valuable credential that reflects your commitment to learning and your ability to apply machine learning concepts in real-world scenarios.

During the 12-Week Machine Learning for Beginners course, you’ll have access to a variety of support resources to help you succeed:

• Instructor Support: Our instructors are available to answer questions, provide clarifications, and offer guidance throughout the course. You can reach out to them through the course platform.

• Teaching Assistants: Teaching assistants are also available to help with more detailed queries, especially related to assignments and projects.

• Community Forum: You’ll have access to a community forum where you can interact with fellow learners. This is a great place to discuss concepts, share insights, and collaborate on projects.

• Live Q&A Sessions: We offer regular live Q&A sessions where you can ask questions directly to instructors and get real-time feedback.

• Email Support: If you encounter technical issues or have questions about course logistics, our support team is available via email to assist you promptly.

These resources are designed to ensure you have the help you need, whenever you need it, so you can focus on learning and making progress.

Yes, the 12-Week Machine Learning for Beginners course is designed to be flexible, allowing you to learn at your own pace. While the course is structured to be completed in 12 weeks, you have the option to move through the materials as quickly or as slowly as you need, based on your personal schedule. All course materials, including lectures, readings, and assignments, are available on-demand, so you can study whenever it’s most convenient for you. Whether you want to complete the course in the recommended timeframe or take a bit longer, you’ll have continued access to the content to support your learning journey.

If you fall behind or need extra time to complete the course, don’t worry. We understand that life can be unpredictable, and the 12-Week Machine Learning for Beginners course is designed with flexibility in mind. You’ll continue to have access to all course materials even after the official 12-week period ends, allowing you to catch up at your own pace. Additionally, you can revisit lectures, assignments, and projects as often as needed. Our support team and instructors are also available to help you get back on track if you need additional guidance or motivation.

During the 12-Week Machine Learning for Beginners course, you’ll work on several hands-on projects designed to reinforce the concepts you learn each week. These projects will include:

• Data Preprocessing: Cleaning and preparing datasets for analysis, including handling missing data, normalization, and feature selection.
• Regression Models: Building and evaluating regression models to predict outcomes based on data, such as predicting housing prices.
• Classification Tasks: Implementing classification algorithms, such as decision trees or logistic regression, to categorize data into different classes.
• Clustering: Using clustering techniques like k-means to group similar data points together.
• Capstone Project: In the final weeks, you’ll complete a capstone project that integrates all the skills you’ve learned. This project will involve solving a real-world problem using machine learning, and you’ll be able to showcase this work in your professional portfolio.

These projects are designed to be practical and relevant, giving you the experience needed to apply machine learning techniques in real-world scenarios.

For the 12-Week Machine Learning for Beginners course, you’ll need access to the following tools and software:

• Google Colab: This cloud-based platform allows you to run Jupyter Notebooks without needing to install anything on your local machine. It’s perfect for coding assignments and projects, especially if you want to avoid the hassle of setup.
• GitHub: We use GitHub for version control and project collaboration. You’ll learn how to manage your code and share your work with others using this platform.
• Jupyter Notebooks: If you prefer working locally, Jupyter Notebooks offer an interactive environment for writing and running Python code. It’s a great tool for documenting your work and visualizing data.
• Anaconda Distribution: We recommend installing Anaconda, which provides an easy setup for Python and essential libraries. It includes Jupyter Notebooks, making it simple to get started on your local machine.
• Python Libraries: The course will heavily utilize Python libraries, including:
  • Scikit-learn: For building and evaluating machine learning models.
  • Pandas: For data manipulation and analysis.
  • NumPy: For numerical computations and handling arrays.
  • Matplotlib: For creating visualizations to better understand your data.

All these tools are free and widely used in the industry, ensuring that you gain experience with the most relevant technologies in the field of machine learning. Detailed setup instructions and guidance will be provided during the course.

At ML Skills Academy, we’re committed to helping you not only learn machine learning but also advance your career. Our career guidance support includes:

• Resume and LinkedIn Optimization: We offer tips and resources to help you update your resume and LinkedIn profile, highlighting the skills and projects you’ve completed during the course.

• Portfolio Development: Throughout the course, you’ll work on hands-on projects and a capstone project that can be showcased in your portfolio. We provide guidance on how to present these projects effectively to potential employers.

• Interview Preparation: We provide resources and mock interview sessions focused on machine learning roles, helping you prepare for technical and behavioral questions.

• Job Search Assistance: While we don’t guarantee job placement, we do offer advice on how to search for jobs in the field of machine learning, including where to look and how to network within the industry.

• Alumni Network: After completing the course, you’ll have access to our growing alumni network, where you can connect with other professionals, share job opportunities, and seek advice as you navigate your career.

This support is designed to help you transition smoothly into a machine learning role and make the most of the skills you’ve acquired.