JOIN THE MOST IN-DEMAND PROFESSION ON THE PLANET
$60.53 Billion
Market Worth by 2027
200,000 to 240,000
More Job Openings by 2027
80 to 85%
Growth by 2027
$154,990
Median Salary
ABOUT THIS COURSE
Machine learning engineers design and develop data intensive applications using powerful algorithms to help make business critical decisions. By learning the fundamentals of machine learning, you’ll be able to understand the main principles of data science and discover the world of Artificial Intelligence, as well as developing your own intelligent predictive models and systems.
Built on real world data from engineers working at top companies, this Skill Plan will teach you the vital skills needed to excel in Machine learning today.
Intern Program
When you graduate, you could work remotely as a freelancer or as a full-staff at GreaterHeight Academy for up to 3–4 months as a paid intern.
Certificates
The course is a package of more than 60 hours of instructor-led training and 100+ hours of hand-on. Once you meet the requirements of the program, you will receive Greaterheight Academy's certificate stating that you have acquired the skillset of a Machine Learning Engineer.
1-on-1 Mentorship
You will get one-on-one help from our mentor(s) and student instructors who will be in charge of reviewing your codes and all of your exercises and project assignments at Greaterheight Academy.
Develop Your Skill
Become an expert in Machine Learning Engineering course and also build production-grade websites, APIs, and data-driven Apps while collaborating with classmates on a range of projects.
Who Should Attend This Course
Being a Machine Learning Engineering professional is the perfect amalgam of experience, data-mining knowledge, and the correct tools/technologies. It is a good career choice for both newbies and experienced professionals who have industry knowledge. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue this path. We would recommend this path strongly for professionals in the following roles:
- Beginners who want to become a Machine Learning Engineers
- IT, Bank managers, Marketing and Supply-Chain-Network Managers
- Freshers into Robotics and Apps development
CAREER SUPPORT
We provide each of our "Become A Machine Learning Engineer" graduates with access to job readiness training, connections to employers and opportunity to hone new skills.
Job Preparation
Build a strong resume with one-on-one coaching support. Learn how to present your code and discuss open source contributions.
Career Resources
Visit development teams at local companies. Attend panel discussions with industry experts.
Networking Opportunities
Showcase your work to potential employers in our global network. Get to know members of your local tech community.
STUDENT LIFE
We break up our daily schedule with a mix of presentations, interactive labs and project collaboration, no two days look exactly alike, but here's an example of what your day could look like on campus.
9
am
Review
Group Review
Daily review and code exercises that reinforce concepts and activities
10
am
Class
Instructor-guided Lessons & Activities
Learn key objectives through lectures, discussions, and activities
12
noon
Lunch
Panel Discussion
Hear from industry insiders during talks and panel discussions (recurring)(Optional)
2
pm
Labs & Exercises
Student-guided Group Activities
Practice new skills, work on labs solo or in groups, & receive instructions on key topics.
5
pm
One-on-Ones
Catch-up on Goals & Progess
Personal review and support from instructors
6
pm
Homework
Panel Discussion
Evening TAs are on hand to support the class in completing daily assignment and review exercises
Career Services
Our experienced team works directly with each student to ensure they are able to excel in their career search and negotiate multiple offers.
Online Presence
By graduation, you will have a strong, unique Machine Learning Engineer Programming portfolio, online profiles and a resume that reflects your value in the job market.
98%
Graduate Hiring Guaranteed
N150,000+
Avg Graduate Salary
50+
Partners & Collaborators
Online Presence
Our instructional staff conducts mock interviews, training exercises and role-play sessions designed to help you tackle the job interview.
WHAT YOU WLL LEARN
Gain the skills you need to land as a Machine Learning Engineer. GreaterHeight Academy teaches the in-demand skills you need to a Machine Learning Engineer in just 6 to 12 months, and you will learn the following from fundamentals through advance, depending on your receptiveness to teaching and mentoring:
Machine Learning Fundamentals
Jump into machine learning with the most popular and industry accepted data science languages: Python and R. Machine Learning Essentials provides the foundations for you to understand the main principles of data science and discover the world of Artificial Intelligence. Develop your own intelligent applications and systems using big data and learn how to program and run predictive algorithms confidently enough to tackle difficult day-to-day machine learning tasks.
What will I be able to do?
Leverage Python's most powerful open source libraries for deep learning, data wrangling, and data visualization;
Harness the power of R to build common machine learning algorithms; Explore how to use various machine learning
models to ask different questions; Discover hidden structures in data using clustering; and Evaluate and improve the
performance of machine learning models.
The Course includes:
Python Machine Learning
Machine Learning with R
Mastering Machine Learning with scikit-learn
Statistical Machine Learning
This Course combines both the art of designing good learning algorithms and the science behind the analysis. Statistical Machine Learning merges statistics with the computational sciences to reflect modern machine learning techniques. In this card, you’ll learn to apply the foundations of statistical techniques to problems in data science and tackle increasingly large data streams at scale. Learn all about predictive analytics, the Bayesian approach, probability, the Gaussian processes, Graphical models, Bayesian optimization, and much more.
What will I be able to do?
Discover the techniques required to build state-of-the art machine learning models, Understand the statistical and mathematical
concepts behind predictive analytics, Perform Bayesian Inference on massively large data sets, Work with Bayesian networks to
infer the probability distribution, and Learn how graphical models can provide crucial insights.
Advanced Machine Learning
This Course is designed to truly give you the skills to master machine learning; you’ll dive into advanced pattern recognition and get an in-depth coverage of cutting edge techniques in machine learning, as well as their underlying theory.
What will I be able to do?
Explore the most powerful languages in data science, including R, Python, and Julia; Perform real-time machine learning with Spark Streaming; See the powerful mechanism of seamless CPU and GPU usage with Theano; Work with Keras to beautify your neural network designs; and Dive deeper into polyglot persistence and semantic data.
The Course includes:
Deep Learning with Python
Machine Learning with Spark
Practical Machine
Testing and Optimizing Machine Learning Systems
When you have business-critical decisions being determined by Machine Learning systems, it is vital that you know how to select, test, and optimize the best algorithms and models for the job. In this Course, you will discover how quantify your models to drive real improvement in your business.
What will I be able to do?
Implement test-driven development concepts for machine learning, Discover simpler approaches to common machine learning
algorithms, Learn how and when to implement Probabilistic Graphical Models and Dynamic Bayesian Networks, and Select the
appropriate model and algorithm for the problem at hand.
The Course includes:
Test-Driven Machine Learning
Mastering Probabilistic Graphical Models Using Python
Data Mining Fundamentals
Learn the fundamentals and the complexities of different data types. This course provides you with a diverse set of problems and solutions in data mining. Analyze big data sets, extract patterns, and build the right models that have a positive impact on your results. Learn advanced techniques with both Python and R, such as text, time series, discrete sequences, graph data, and social networks.
What will I be able to do?
Design and develop data mining applications using a variety of datasets, Familiarize yourself with the crucial data cleaning
processes, Extract data from web pages with simple Python programming, Perform sentiment analysis, and Develop recommendation
systems.
The Course includes:
Learning Data Mining with Python
Mastering Social Media Mining with R
Web Scraping with Python
Natural Language Processing Basics
One of the hardest techniques for a system to master is for it to “understand” concepts and phrases in a meaningful way. This course covers a broad range of topics in natural language processing, including information extraction, word, text classification, and sentiment analysis. We will also introduce key data mining techniques and their underlying principles in machine learning. This card will help you label relationships between words, such as subjects and objects, through efficient algorithms.
What will I be able to do?
Train NLP models to address domain-specific problem areas, Construct solutions to identify parts of speech within sentences,
Clean and wrangle text using tokenization, Extract data from any source to perform real-time analytics, and Learn key techniques
in Python to perform web crawls.
The Course includes:
Natural Language Processing with Java
NLTK Essentials
Learning Scrapy
Working with Big Data
Discover the hype surrounding the big data phenomenon. In this course, learn to find hidden meanings and patterns from real-world data and learn vital problem-solving skills. If you don’t know how to work with and manage your data properly, you risk missing the signal in the noise. Working with Big Data shows you how to store, access, and analyze your data to become proficient with key technical terms and big data tools and applications.
What will I be able to do?
Write distributed applications using the MapReduce framework, Conduct batch and real-time data analysis, Get essential techniques
when working with HDFS and Yarns, Discover Spark stream processing via Flume HDFS, and Perform Spark-based graph processing using
Spark GraphX.
The Course includes:
Learning Hadoop 2
Mastering Apache Spark
Download our full curriculum to see what we teach week-by-week!
APPRENTICESHIP
Beyond the classroom, the Apprenticeship emphasizes real-world work experience, collaboration with a team of developers, project planning and management, and pair programming, as well as interview and resume preparation. By building professional experience into the GreaterHeight Academy program, we ensure that our developers continue to grow after class-room interactions. Every day apprenticing makes you more competitive in the industry and more likely to land the Machine Learning Engineer position of your dreams.
GreaterHeight
Technologies
Our independent GreaterHeight Technologies, GreaterHeight Technologies, to provide GreaterHeight Academy graduates with the professional experience they need to launch their coding careers. Our developers deliver polished web applications to clients.
Work Alongside
Experienced Devs
During your Machine Learning Engineer apprenticeship, you'll pair program with the agency's more experienced Business Analyst. This opportunity allows apprentices to learn from senior devs hands-on, plus gain experience programming in pairs - a common industry practice.
Job Prep
Curriculum
Your apprenticeship with Greaterheight Academy also includes our three-part job-prep curriculum. You'll learn how to land interviews, improve the soft skills employers look for, and master Machine Learning Engineering Development and technical topics likely to come up in interviews.
BENEFITS
GUARANTEED
EXPERIENCE
Guaranteed way to gain real-world experience in your new profession and build an impressive Machine Learning Engineer Stack portfolio.
TEAM
COLLABORATION
Learn skills you can't get in a classroom: team collaboration, working with clients, agile, and more.
PROFESSIONAL
MENTORING
Gain knowledge from experienced professional developers throughout your apprenticeship.
SELF
CONFIDENCE
Gain confidence and prove to yourself that you are now a professional Machine Learning Engineer Stack developer.
TUITION
N550,000
Financing Available
Financing plans available through Greaterheight Academy and our hand-selectd financing partners, Skins Funds. Repayment period ranged from 0-5years with monthly payments as low as N20,000.00. Contact your Student Advisor for details.
We stand by your results
Get a job creating software upon graduation, or we will refund your tuition in full. See details
Payment Plans
Tuition can be paid upfront or over six installments. The installment plan: one payment of 50% of the program cost fee upon enrollment, and monthly installments of 10% until the Tuition is fully paid. We accept credit cards, debit cards, checks, and PayPal.
Scholarships
Diversity and Merit Based Scholarships available. Attend an info session to learn more.
Refund Policy
We'll provide you with a full refund if you drop out within 7 days of starting your course. If you choose to drop out later, you will receive a pro-rated refund based on the number of days you've spent in the program, minus a non-refundable 10% of program cost fee.
FUND YOUR FUTURE
Need payment assistant? or financing options allow you to focus on you goals instead of the barrier that stop you from reaching them.
Future Finance
Apply for fixed and term based merit loan
GET THE INFO FROM AN EXPERT
Dive deep into the curriculum, the course structure, and what you can achieve from a course mentor.
See if this program is a fit for you. Meet the GreaterHeight team, get an overview of the program curriculum, and chat with other students thinking about this program.
Become Machine Learning Engineer information Session
By providing us with your email, you agree to the terms of our Privacy Policy and Terms of Services.
FAQs
We love questions, almost as much aswelove providing answers.Here are a few samplings of what we're typically asked, along with our responses.
By the end of this lesson, you will be able to design a Web Apps and Predict certain behaviours and characters as you master the followings:
- Leverage Python's most powerful open source libraries for deep learning, data wrangling, and data visualization
- Harness the power of R to build common machine learning algorithms
- Explore how to use various machine learning models to ask different questions
- Discover hidden structures in data using clustering
- Evaluate and improve the performance of machine learning models
- Discover the techniques required to build state-of-the art machine learning models
- Understand the statistical and mathematical concepts behind predictive analytics
- Perform Bayesian Inference on massively large data sets
- Work with Bayesian networks to infer the probability distribution
- Learn how graphical models can provide crucial insights
- Explore the most powerful languages in data science, including R, Python, and Julia
- Perform real-time machine learning with Spark Streaming
- See the powerful mechanism of seamless CPU and GPU usage with Theano
- Work with Keras to beautify your neural network designs
- Dive deeper into polyglot persistence and semantic data
- Implement test-driven development concepts for machine learning
- Discover simpler approaches to common machine learning algorithms
- Learn how and when to implement Probabilistic Graphical Models and Dynamic Bayesian Networks
- Select the appropriate model and algorithm for the problem at hand
- Design and develop data mining applications using a variety of datasets
- Familiarize yourself with the crucial data cleaning processes
- Extract data from web pages with simple Python programming
- Perform sentiment analysis
- Develop recommendation systems
- Train NLP models to address domain-specific problem areas
- Construct solutions to identify parts of speech within sentences
- Clean and wrangle text using tokenization
- Extract data from any source to perform real-time analytics
- Learn key techniques in Python to perform web crawls
- Write distributed applications using the MapReduce framework
- Conduct batch and real-time data analysis
- Get essential techniques when working with HDFS and Yarns
- Discover Spark stream processing via Flume HDFS
- Perform Spark-based graph processing using Spark GraphX
View All FAQs
