Practical Data Science with Amazon SageMaker Course in Ghana

Master ML with Amazon SageMaker

Get real-world insights from certified instructors

Apply machine learning to tackle real business challenges

Gain in-demand ML skills and boost your job prospects

Learn at your own pace with flexible, instructor-led sessions

Master the full ML workflow and its practical applications

Convenient and hassle-free payment plans

4.8/5

5469 EnrolledEnrolled Learners

4.8/5

5469 EnrolledEnrolled Learners

Overview

What you will learn:

Learn data preparation techniques using Amazon SageMaker Data Wrangler
Train models with powerful algorithms like XGBoost on Amazon SageMaker
Evaluate and fine-tune models with hyperparameter optimization in SageMaker
Deploy models to real-time endpoints with Amazon SageMaker for seamless integration
Master MLOps practices to automate and monitor model deployment
Gain hands-on experience in no-code machine learning with Amazon SageMaker Canvas

Upcoming sessions

Curriculum

Benefits of machine learning (ML)

Types of ML approaches

Framing the business problem

Prediction quality

Processes, roles, and responsibilities for ML projects

Data analysis and preparation

Data preparation tools

Demonstration: Review Amazon SageMaker Studio and Notebooks

Hands-On Lab: Data Preparation with SageMaker Data Wrangler

Steps to train a model

Choose an algorithm

Train the model in Amazon SageMaker

Hands-On Lab: Training a Model with Amazon SageMaker

Amazon CodeWhisperer

Demonstration: Amazon CodeWhisperer in SageMaker Studio Notebooks

Model evaluation

Model tuning and hyperparameter optimization

Hands-On Lab: Model Tuning and Hyperparameter

Optimization with Amazon SageMaker

Model deployment

Hands-On Lab: Deploy a Model to a Real-Time Endpoint

and Generate a Prediction

Responsible ML

ML team and MLOps

Automation

Monitoring

Updating models (model testing and deployment)

Different tools for different skills and business needs

No-code ML with Amazon SageMaker Canvas

Demonstration: Overview of Amazon SageMaker Canvas

Amazon SageMaker Studio Lab

Demonstration: Overview of SageMaker Studio Lab

(Optional) Hands-On Lab: Integrating a Web Application

with an Amazon SageMaker Model Endpoint

Meet your Trainer

Our Trainers

Learners Point has a reputation for high-quality training that makes a difference in people's lives. We undertake a practical and innovative approach to working closely with businesses to improve their workforce. Our expertise is wide-ranging with ample support from our expert trainers who are globally recognized and hold a diverse set of experiences in their field of expertise. We are proud of our instructors who take ownership of our distinctive and comprehensive training methodologies, help our students imbibe those with ease, and accomplish gracefully.

We at Learners Point believe in encouraging our students to embark upon a journey of lifelong learning and self-development, with the aid of our comprehensive and distinctive courses tailored to current market trends. The manifestation of our career-oriented approach is what we assure through a pleasant professional enriched environment with cutting-edge technology, and an outstanding while highly acknowledged training staff that uses up-to-date methodologies and quality course material. With our aim to mold professionals to be future leaders, our industry expert trainers provide the best in town mentorship to our students while endowing them with the thirst for knowledge and inspiring them to strive for professional and human excellence.

Learning Outcomes

Successful completion of the training will help professionals in the following ways:

Master data preparation with SageMaker Data Wrangler to streamline data processing

Train models using advanced algorithms like XGBoost and fine-tune with hyperparameter optimization

Deploy machine learning models to real-time endpoints with Amazon SageMaker for seamless predictions

Implement MLOps practices for automating, monitoring, and managing model deployments

Gain practical experience in no-code machine learning using SageMaker Canvas

Ready to get started?

Learners Point Certificate

Earn a Course Completion Certificate, an official Learners Point credential that confirms that you have successfully completed a course with us.

KHDA Certificate

Earn a KHDA attested Course Certificate. The Knowledge and Human Development Authority (KHDA) is the educational quality assurance and regulatory authority of the Government of Dubai, United Arab Emirates.

Overall ratings by our students

Related courses

Learn now, pay later

Dive into your course now and pay in installments

Frequently asked questions

Our Practical Data Science with Amazon SageMaker course in Ghana teaches you how to use AWS SageMaker to create, train, and implement machine learning models. Professionals gain knowledge of MLOps procedures, real-time deployment, model optimization, and data preparation. We assist you in becoming proficient with SageMaker products such as SageMaker Canvas, XGBoost, and Data Wrangler.

Our course empowers you with the hands-on skills you need to assume leadership positions in data science. With mastery over data preparation, model construction, and deployment, you will be well-prepared for leadership roles like Lead Data Scientist, ML Team Manager, or AI Specialist.

By achieving this certification, you have the freedom to pursue data science, machine learning, and AI career opportunities. You can work in different fields, such as auditing, taxation, consulting, software development, and data analysis. You may also consider leadership positions in AI and data engineering.

To join our Practical Data Science with Amazon SageMaker course, professionals must have some knowledge of programming principles, preferably Python. Although no degree is necessary, data science, computer science, or a related degree will be advantageous. An elementary understanding of statistics and data analysis will also be helpful.

Although experience with machine learning in the past is not a requirement, knowledge about programming, specifically Python, will simplify the learning process. The course is crafted to suit beginners as well as users who have intermediate experience with data science.

After you complete the course, you will have an edge over others in the job market. The course provides you with practical skills in machine learning, model deployment, and data science, qualifying you for positions like Data Scientist, Machine Learning Engineer, AI Specialist, and Cloud Engineer.