AI201: Machine Learning and Deep Learning

Learn the concepts of machine learning and deep learning with Python from experienced data scientists in Singapore.

✅  Hybrid instructor-led classes
✅  Basic and intermediate machine and deep learning concepts
✳️  Build your own data analytics projects on real-world datasets
⭐ Rated 4.8/5 on SwitchUp and Google

Data Science Nanodegree

Data Analytics Nanodegree

Data Science Nanodegree

Earners of this badge have demonstrated proficiency in interpreting big data, implement advanced computational techniques, and utilise linguistic algorithms using Python.

 Earners have completed AI101, AI201, and AI301
 Direct admission into Buidlnaut internship programme
 Increased employment chances
AI101
Data Analytics and AI with Python
⧖    18 instructional hours
△   Beginner level
ⓘ   No prior knowledge required
AI201
Machine Learning and Deep Learning
⧖    24 instructional hours
△   Intermediate level
ⓘ   AI101 or equivalent knowledge
AI301
Natural Language Processing with Python
⧖   24 instructional hours
△   Advanced level
ⓘ   AI201 or equivalent knowledge

Data Analytics Nanodegree

Earners of this badge have demonstrated proficiency in analysing, visualising, and interpreting data, utilising Python, and implementing machine learning solutions.

 Earners have completed DAT101, AI101, and AI201
 Direct admission into Buidlnaut internship programme
 Increased employment chances
DAT101
Data Analysis and Visualisation
⧖   18 instructional hours
△   Beginner level
ⓘ   No prior knowledge required
+
AI101
Data Analytics and AI with Python
⧖    18 instructional hours
△   Beginner level
ⓘ   No prior knowledge required
AI201
Machine Learning and Deep Learning
⧖    24 instructional hours
△   Intermediate level
ⓘ   AI101 or equivalent knowledge

Growing Demand For Data Scientists

Machine learning and deep learning are at the forefront of today's technological revolution. Businesses across the spectrum leverage these advanced algorithms to derive insights, enhance decision-making, and propel innovation. Consequently, the quest for proficient machine learning engineers and data scientists is intensifying.

By mastering machine learning and deep learning with Python, you'll acquire the capabilities to develop predictive models, unlock patterns in massive datasets, and design neural networks that can perceive and think akin to the human brain.

Don't just hear it from us

"I had an incredible experience at this course. I never thought that after such a short amount of time I would be able to create a simple web server from scratch. One of the main pros for me have been the attentive instructors."

VICTORIA TEO
Senior UX Consultant

"Attending bootcamp gave me guidance and direction when I was trying to transition into a tech career. Metacamp has great instructors and their lectures were awesome. Coding challenges and projects helped reinforce the concepts. I would highly recommend Metacamp to aspiring software engineers."

ATSUSHI YAMAGUCHI
Tech Presales

"I wanted to learn more about blockchain that I was already interested in but had no idea where to start. Metacamp was the perfect answer. Metacamp is an excellent platform for people to gather, learn, and share their experiences."

lim qi jie
Co-Founder, TableFi

Industry expert instructors from AWS, Microsoft, OKX, ...

Attend live classes online outside of working hours

Graduate with a blockchain-verified certificate

Build and pitch your capstone project during demo day

Dedicated career support and matching with partners

4.8 / 5 ⭐
5 / 5 ⭐

Machine Learning and Deep Learning Course Details

Metacamp's Machine Learning and Deep Learning with Python course in Singapore is designed to provide students with the latest techniques and best practices in the rapidly evolving fields of artificial intelligence. Delving deep into pivotal Python frameworks and tools, learners will apply their newfound knowledge to an array of projects, addressing tangible real-world problems using advanced algorithms.

What to expect?

Learn new concepts and tools through expert-led lectures, discussions, assignments and projects

Complete all assignments and receive a certificate of completion in the form of an NFT at the end of the course

Receive individualised feedback and support from your instructional team with free 1-on-1 consultations

Be part of a community where members can leverage connections with alumni, instructors and experts

Machine Learning and Deep Learning Course Schedule

The schedule for this course is currently unreleased on our website. We encourage you to join our waitlist so that you will be prioritised and notified once our schedule is out. Feel free to reach out to us via email at team@metacamp.so for any enquiries!

Machine Learning and Deep Learning Course Curriculum

Module 1: Introduction to Data
  • What is Big Data
  • Characteristics of Big Data
  • Economic benefits of Big data
  • Different types of Analytics
  • Data Analytics use cases
  • Data Analytics vs Data Science
  • Data tools and software
  • Why Python?
Module 2: Python I
  • Navigating Jupyter Notebook
  • Writing first programme
  • Different data types in Python
  • Variables assignment
  • Operators
  • String slicing and manipulation
  • List slicing and manipulation
  • Iterations with for loops
Module 3: Python II
  • Iterations with while loops
  • Write control flow statements
  • List slicing and manipulation
  • Dictionary slicing and manipulation
  • Define own custom functions
  • Nested iterations
  • Art of debugging
Module 4: Complete Pandas and NumPy
  • Creating NumPy arrays
  • NumPy vectorisation
  • Manipulating data in NumPy
  • Calculating statistics with NumPy
  • Boolean techniques with NumPy
  • Preliminary exploration with Pandas
  • Manipulating data in Pandas
  • Frequency analysis in Pandas
  • String manipulation in Pandas
  • Configuring Panda stable
  • Handling null values
  • Applying row-wise functions
  • Merging multiple dataframes
Module 5: Data Analysis with Python
  • Plotting basic charts on matplotlib
  • Modifying axis, labels and title
  • Plotting multiple plots
  • Adding color and create legend
  • Barplots
  • Histogram
  • Boxplots
  • Kernel density plot
  • Setting style and despine
  • Conditional plotting
  • Overlaying plots
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