The Hacker Collective | Learn Data Science!
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Monthly: RM500 / USD120
Data Science

Duration: 4 months

description
curriculum
About this course

This course is an introduction to finding insights and telling stories through data. You will be given a hands-on experience with data analysis tools and even build your own machine learning models. This programme is suitable for people of all skill levels. And No, you don't need a university degree and 3 years of your life. What you need is passion, commitment and a learning group. Friends and mentors that can guide you and journey with you together towards your goal of data science success. By the end of this course, you will gain key skills needed to become a professional Data Scientist.

Mentors
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Mentor
FAQs
Can I just enroll in a single course? I'm not interested in all the other amazing courses offered.

Definitely! Though we do give offers every now and then for participants who take up more courses with us.

This sounds cool. But what can I expect to do after the programme?

Depending on your skill level, you could go on to build your own tech startup, freelance, work remotely, or be employed as a software developer. The learning never stops for software developers! We believe you can become a junior developer or at the very least intern at a firm before becoming a full time developer! The Hacker Collective team is always working with business partners to provide placement positions for our graduates.

What background knowledge is necessary?

Basic computer knowledge would be great, but not necessary. We tailored the course to be beginner friendly, also do take note that we expect at least 15 hours of hard work on your end throughout the week, on top of our 3 hours weekly meetups.

Any opportunities to meet up with other people in the community?

Of course! We're working on monthly Townhall Sessions, where the community come together and build projects together with The Hacker Collective members, and weekly open live sessions on Zoom. This would be the perfect opportunity for everyone from the THC community to network and meet people from other groups!

How much will I be paid at tech internships?

Depending on the company and country, in Malaysia it's approximately RM800-RM1500.

What if I need help when I'm trying to learn myself at home?

Feel free to contact your mentors anytime via Discord! They will be there to help answer your programming questions for the rest of the week when you're not at the HiPO meetup!

Syllabus
  • Regression
  • Clustering
  • Fundamental Math of Data Science
  • Data Science Frameworks
  • Data Exploration
  • Data Modeling
  • Machine Learning


Tools We Use
  • Python
  • Scitkit-Learn
  • Pandas
  • TensorFlow
  • Pytorch
  • Matplotlib
Month 1: DATA SCIENCE PRIMER WITH EXCEL
1/4
Beginner

We've put together weekly challenges & monthly group projects for you to get your hands dirty and really execute on the work alongside your groupmates.

  • Data Science With Excel
    • Data science lifecycles
    • K-means clustering
    • Linear & non-linear algorithms
  • Challenge 1: Build a k-means cluster with excel
  • Challenge 2: Building optimization algorithms in excel
  • Challenge 3: Data cleansing and visualisation with any dataset
Month 2: DATA SCIENCE WITH PYTHON
2/4
Beginner

We've put together weekly challenges & monthly group projects for you to get your hands dirty and really execute on the work alongside your groupmates.

  • Data Science With Python
    • Pandas, Matplotlib
    • Statistics, Probability, Linear Regression
    • Data Visualisation
    • ReLU activation functions
  • Project 1: Complete a basic data science project (with pandas and matplotlib)
  • Project 2: Complete a data set analysis with Pandas, Matplotib
  • Challenge 3: Data cleansing and visualisation with any dataset
Month 3: SUPERVISED LEARNING
3/4
Intermediate

Learn the major algorithm concepts of supervised learning whilst using sci-kitlearn.

  • Overview of Supervised Learning
    • Algorithms: Classificaiton
    • Algorithms: Regression
    • Machine learning models & predictions
  • Project: Complete a whole project using tools learned
  • Challenge: Gather, Clean, Parse, Model and Generate Insights of any dataset
Month 4: UNSUPERVISED LEARNING
4/4
Intermediate

Understand neural nets, how it works and build one with Python. Then use Keras and TensorFlow to build a basic neural net model.

  • Overview of Unsupervised Learning
    • Clustering
    • Neural Networks
  • Challenge: Kaggle challenge & submission
  • Final Project: Build a deep learning neural net to model and predict non linear data
Reviews

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Sep 29, 2017 at 9:48 am

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Sep 29, 2017 at 9:48 am

Nam egestas lorem ex, sit amet commodo tortor faucibus a. Suspendisse commodo, turpis a dapibus fermentum, turpis ipsum rhoncus massa, sed commodo nisi lectus id ipsum. Sed nec elit vehicula.

Sep 29, 2017 at 9:48 am

Nam egestas lorem ex, sit amet commodo tortor faucibus a. Suspendisse commodo, turpis a dapibus fermentum, turpis ipsum rhoncus massa, sed commodo nisi lectus id ipsum. Sed nec elit vehicula.

Members

Lorem ipsum dolor sit amet, te eros consulatu pro, quem labores petentium no sea, atqui posidonium interpretaris pri eu. At soleat maiorum platonem vix, no mei case fierent. Primis quidam ancillae te mei.