Data Science Online Course with Certification

Q: What is the difference between machine learning and deep learning?

1. Hardware Dependence Deep learning requires more powerful hardware to perform learning within a reasonable time. Machine learning is less dependent on hardware.2. Learning Time Deep learning requires a longer learning time compared to the learning time of machine learning.3. Task Execution Time After the learning process is completed, deep learning performs the required task much faster than machine learning.4. A machine learning system operates based on a certain algorithm, whereas a deep learning system operates without one.

Q: What does a data scientist know?

Data scientists have knowledge and experience working with1. Machine Learning algorithms, such as SVM (Support Vector Machine), Decision Trees, etc.2. Various types of databases (relational and/or non-relational), like SQL, MongoDB, etc.3. Different programming languages, such as Python, R, etc.4. Messy, outdated, and missing data.5. Complex and multifaceted functions.

Data Science Course Overview

Our Data Science online course is meticulously designed to propel you into a professional career in data science, one of the most in-demand fields in today's tech-driven economy. Focused on the core principles of data analysis, this course dives into statistical modelling, predictive analytics, machine learning, and data visualization techniques. You'll master essential tools and programming languages including Python and SQL, which are crucial for handling big data environments effectively, equipped with valuable insights.

The course curriculum is structured to bridge the gap between theoretical knowledge and practical expertise. Through collaborative projects and case studies, you will apply your skills to real-world data challenges, gaining the experience needed to solve complex problems. This hands-on approach not only enhances your understanding but also prepares you to enter the industry as a skilled data scientist, ready to contribute to and lead data-driven projects in any organization.

Skills You Will Gain Completing Our Data Science Training Program

Expertise in Python and SQL for data manipulation and analysis.
Proficiency in using machine learning algorithms to solve business problems.
Ability to create impactful data visualizations and dashboards.
Skills in big data technologies for handling large-scale data sets.
Understanding of statistical models for predictive analytics.

As a Qualified Our Data Science Course Graduate, You’ll Be Prepared for Roles Such As:

Data Scientist
Data Analyst
Machine Learning Engineer
Business Intelligence Analyst
Quantitative Analyst

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Industries You’ll Be Able to Work in With Our Online Data Science Course

Technology and Software
Financial Services
Healthcare
Marketing and Sales
Government and Public Sector

Why Study Data Science at Embedded Academy

Job placement

Secure a fulfilling role at a top technology company upon graduation.

Internship

Gain practical, on-the-job experience at a tech company as part of your training.

1x1 lessons

Personalized guidance & support as part of our mentoring process to ensure your success.

Hybrid Learning

Self-paced online courses and live instructor-led sessions for a full learning experience.

Convenient payment methods

Flexible options to make your tech education accessible.

Career Advisory & guidance

Your personalized roadmap to professional success, guided by industry experts.

Admission Requirements

Basic computer skills (operating Windows OS).
Basic knowledge in mathematics and statistics (no need to be a mathematician, just the basics).
No previous programming experience is required.

Admission Requirements

Basic computer skills (operating Windows OS).
Basic knowledge in mathematics and statistics (no need to be a mathematician, just the basics).
No previous programming experience is required.

Data Science Curriculum

Full Track

Standard Track

Self-Designed Track

Data Science Track: From Novice to Expert

Launch your career in Data Science with our most comprehensive educational track. This program is meticulously designed to provide you with an all-encompassing understanding of the field, ensuring you achieve the highest level of expertise.
Key Features:

Holistic Learning: Engage with all modules, gaining a thorough and well-rounded proficiency in Data Science .
Beginner-Friendly: Tailored for newcomers with little to no prior experience, providing a supportive environment for those taking their first steps into this dynamic field.
In-Depth Immersion: Dive deep into the subject matter over a 9 to 12-month period, allowing ample time for concept absorption and practical application.
Extensive Curriculum: Benefit from an impressive 335 academic hours of instruction, covering a wide array of essential topics and cutting-edge techniques.

This track is your gateway to becoming a proficient Data Science expert, equipping you with the knowledge, skills, and hands-on experience needed to excel in this rapidly evolving and in-demand area of technology.

Machine Learning & Data Science	Course duration
Machine Learning Fundamentals Course	25 academic hours
Machine Learning can adapt its behavior based on past programming activity and feedback. This course introduces ML theory and foundations as well as best practices.
Scientific Python Course	30 academic hours
Python offers a wide range of libraries used for ML (NumPy, SciPy, Matplotlib, Pandas, etc.) The course teaches how to use these libraries and simplifies the developer's ability to write advanced and reliable code
Machine Learning With Python Course	50 academic hours
Learn how to apply ML Fundamental models using libraries and Python programming language tools.
Deep Learning with TensorFlow Course	50 academic hours
Deep Learning / Deep Neural Networks is considered the most advanced subset of artificial intelligence as it mimics how the human brain works. Here you'll learn how to develop and test Deep Learning models using TensorFlow API.
Software Programming Courses	Course duration
Python Course	90 academic hours
Focusing on Python 3, you’ll learn to program object-oriented, real-industry applications.
SQL Course	30 academic hours
SQL is a special-purpose programming language designed for managing data in a relational database. Learn how to use SQL to store, query, and manipulate data.
AWS Course	35 academic hours
Gain an in-depth understanding of Amazon Web Services architectural principles and services, design and scale AWS Cloud implementations with best practices recommended by Amazon.
GIT (Version Control) Course	25 academic hours
Learn Git’s core features and workflow, different ways to undo changes or save multiple versions, and collaborate with other teams and developers.

Tuition
$10,800 $14,890

Data Science Specialist Track

Elevate your software development expertise with our focused Data Science program. This track is carefully crafted for professionals with prior experience in software and application development, aiming to sharpen your skills in this specialized domain.
Key Features:

Targeted Curriculum: Concentrate solely on modules directly relevant to Data Science , ensuring efficient and applicable learning.
Accelerated Learning: Designed for experienced developers, this condensed track spans 6 to 7 months, allowing you to augment your existing skill set quickly.
Intensive Study: Engage in 155 academic hours of specialized instruction, delving deep into the intricacies of Data Science .

This track offers a streamlined path to mastering Data Science , ideal for seasoned developers looking to expand their expertise or pivot into this high-demand field. Gain the specific knowledge and skills needed to excel in Data Science development and stand out in the competitive tech industry.

Machine Learning & Data Science	Course duration
Machine Learning Fundamentals Course	25 academic hours
Machine Learning can adapt its behavior based on past programming activity and feedback. This course introduces ML theory and foundations as well as best practices.
Scientific Python Course	30 academic hours
Python offers a wide range of libraries used for ML (NumPy, SciPy, Matplotlib, Pandas, etc.) The course teaches how to use these libraries and simplifies the developer's ability to write advanced and reliable code
Machine Learning With Python Course	50 academic hours
Learn how to apply ML Fundamental models using libraries and Python programming language tools.
Deep Learning with TensorFlow Course	50 academic hours
Deep Learning / Deep Neural Networks is considered the most advanced subset of artificial intelligence as it mimics how the human brain works. Here you'll learn how to develop and test Deep Learning models using TensorFlow API.

Tuition: $7575.00

Customizable Data Science Expertise Track

Tailor your tech education with our flexible, modular program. This track allows you to focus on specific areas of interest, creating a personalized learning journey.
Key Features:

Customized Learning: Select only the courses and content you need.
Experience-Based: Ideal for students with prior field experience.
Flexible Duration: Complete in 1 to 3 months, based on your course selection.

Machine Learning & Data Science	Course duration
Machine Learning Fundamentals Course	25 academic hours
Machine Learning can adapt its behavior based on past programming activity and feedback. This course introduces ML theory and foundations as well as best practices.
Scientific Python Course	30 academic hours
Python offers a wide range of libraries used for ML (NumPy, SciPy, Matplotlib, Pandas, etc.) The course teaches how to use these libraries and simplifies the developer's ability to write advanced and reliable code
Machine Learning With Python Course	50 academic hours
Learn how to apply ML Fundamental models using libraries and Python programming language tools.
Deep Learning with TensorFlow Course	50 academic hours
Deep Learning / Deep Neural Networks is considered the most advanced subset of artificial intelligence as it mimics how the human brain works. Here you'll learn how to develop and test Deep Learning models using TensorFlow API.
Software Programming Courses	Course duration
Python Course	90 academic hours
Focusing on Python 3, you’ll learn to program object-oriented, real-industry applications.
SQL Course	30 academic hours
SQL is a special-purpose programming language designed for managing data in a relational database. Learn how to use SQL to store, query, and manipulate data.
AWS Course	35 academic hours
Gain an in-depth understanding of Amazon Web Services architectural principles and services, design and scale AWS Cloud implementations with best practices recommended by Amazon.
GIT (Version Control) Course	25 academic hours
Learn Git’s core features and workflow, different ways to undo changes or save multiple versions, and collaborate with other teams and developers.

Tuition

Payment Plans

As Low As

$330/Month

Meet your instructor

Alex Shoihat

Head of Machine Learning Departments

Alex holds a B.Sc. in Information Systems and an M.A. in Electrical and Electronic Engineering.

As a Machine Learning Engineer at Embedded Academy, Alex specializes in the field of artificial intelligence, applying over 13 years of experience in project development, management, and transitioning from development to production in various domains such as Linux Embedded.

Throughout his career, Alex developed his expertise working with the integration of Machine Learning and Deep Learning in the Computer Vision and Data Analysis field.

Certification

Students must complete the following to be eligible for Data Science certification:

Participation in at least 80% of the course hours
Submission of a final project / final exam with a score of 70 and above
Obligation to submit course assignments, including exercises, homework, and projects

Career Advisory

As part of the professional experience each graduate undergoes we help in integrating them into the high-tech world through our job search assistance, personalized resume building, and placement in a technology company.

Curriculum customization

We'll help you choose and structure the right program most suitable for your needs and career aspirations.

Tech Training

Students who start with no prior knowledge of the field will receive the fundamentals required to complete the course.

Final Project

Working on your course project and internship with experienced developers.

Internship

Get real-world experience adapted to industry standards and requirements with our team of industry-leading engineers.

Job Interview

Graduates get resume-building assistance, interview simulations and career guidance.

What do our graduates say?

Sarah L.
Machine Learning course graduate

AI/ML developer

The Machine Learning course was super practical, from hardcore algorithms to the ethics of AI. Thanks to the professional connections I met during school got me several job offers to check right after I graduate

Paul N.
Machine Learning course graduate

Machine Learning Engineer

I was initially intimidated by the prospect of learning AI and machine learning because I thought I didn’t have enough mathematical knowledge, but throughout the course my instructor made sure I wouldn’t follow behind. It made a huge difference from other times I experienced with online courses.

Howard E.
AI course graduate

AI Product Manager

As a business leader, the AI/ML program has been instrumental in helping me identify opportunities to leverage intelligent technologies. I've been able to upskill my team and implement data-driven strategies that have given us a significant competitive advantage in the market.

Greg B.
Machine Learning course graduate

Robotics and Automation Specialist

I was impressed by the breadth and depth of the AI/ML curriculum. The hands-on projects, mentorship from industry experts, and exposure to real-world case studies have given me the confidence to apply advanced machine learning methodologies to solve real-world problems.

Leonard H.
AI course graduate

Natural Language Processing (NLP) Specialist

As someone with a background in data analysis, the AI/ML course provided me with the selected skills to take my career forward. I'm now fluent in building and deploying sustainable predictive models that drive strategic decision-making paths.

Our graduates work here

FAQ

What are the work stages of a data scientist?

1. Understand the main goal and intermediate objectives of the project.
2. Collect data from various sources.
3. Organize the data at your disposal: cleans, filters, and arranges.
4. Construct a model that theoretically should achieve the project's goals.
5. Train the system on the data portion and evaluate the learning results.
6. Validate the model to achieve the goals with unfamiliar data.
7. In case the system did not sufficiently achieve the goals, start again from the first stage.

What is the difference between machine learning and deep learning?

1. Hardware Dependence: Deep learning requires more 'powerful' hardware to perform learning within a reasonable time. Machine learning is less dependent on hardware.
2. Learning Time: Deep learning requires a longer learning time compared to the learning time of machine learning.
3. Task Execution Time: After the learning process is completed, deep learning performs the required task much faster than machine learning.
4. A machine learning system operates based on a certain algorithm, whereas a deep learning system operates without one.

What does a data scientist know?

Data scientists have knowledge and experience working with:
1. Machine Learning algorithms, such as SVM (Support Vector Machine), Decision Trees, etc.
2. Various types of databases (relational and/or non-relational), like SQL, MongoDB, etc.
3. Different programming languages, such as Python, R, etc.
4. Messy, outdated, and missing data.
5. Complex and multifaceted functions.

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