This course teaches you the fundamentals, use cases, popular algorithms and techniques of Machine Learning.
Get trained by faculty from London Business School
The chief instructor for this course is Peeyush Taori. An ex-Microsoft Data Scientist and a PhD from London Business School, Peeyush consults hedge funds, financial services and media companies in setting up their Big Data & Data Science practices. Peeyush’s ability to simplify complex topics like Spark & Machine Learning makes him popular among students. He is based out of London.
After every session, each concept is illustrated with its application in the real-world. Students get to understand the application of theory via case-studies like movie rating case study, titanic survival prediction data-set, IPL cricket data analysis and many more.
Hands-on exercises make students practice programming languages like Python & R and tools such as Tableau simultaneously as the instructor teaches them. For example, if the concept taught is Linear Regression, then students have access to all the respective files that the instructor is working on and they also get to work on the same.
Projects with Real-World Data-Sets
Each student will undertake projects from real-world data-sets from companies such as Amazon, Twitter, Walmart, Stack Overflow, and other premier organizations. Working on these data-sets will help students cement what they have studied in class.
Students are divided into study groups of 8-10 where students from the same cities are put in the same group. This enables them to solve problems in teams, just like the way it works in the real world. After all, Data Scientists often work on projects in a team. We also have discussion forums, where students can post their queries and have discussions with the other enrolled students.
Complete Study Material
We provide our students with a host of materials all throughout the course. Before each class, many pre-reads, videos and installation guides are given to make the student well-equipped for the class. After every session, assignments are given to test how effectively they have understood the concepts taught. Apart from this, students also get access to the class recordings, a host of knowledge repositories, cheat sheets, PowerPoint presentations, and solutions to frequently asked queries.
Interact with Industry Experts
Industry immersion sessions enable students to interact with Big Data Analytics practitioners from top companies like Twitter, Facebook, Vodafone, Barclays, PwC, Zomato, etc. to make them understand how their organizations use Big Data & Data Science.
Dedicated Student Support
We provide personal assistance and technical support to our students beyond class hours. Our student support team consists of experienced research associates with vast technical knowledge in Data Science and Big Data. They help the students in solving their course-related queries & guiding them through projects.
- Next batch start date: Feb 18th
- Schedule: Sat, Sun (8:00 AM-10:00 AM IST)
- Duration: 5 Weeks
- Mode: Online
- Certification of Completion: Yes
- Certification: Subject to clearing exam
Module 1: Fundamentals & Use Cases 0/2
- 1.1 Machine Learning Fundamentals
- 1.2 Common Use Cases
Module 2: Supervised & Unsupervised Learning 0/1
- 2.1 Understanding Supervised & Unsupervised Learning Techniques
Module 3: Regression 0/4
- 3.1 Regularization & Data Imputation
- 3.2 Linear Regression (One Variable & Multiple Variable)
- 3.3 RMSE. R-squared, Interpreting Residuals
- 3.4 Logistic Regression
Module 4: Clustering 0/4
- 4.1 Classification- Theory
- 4.2 Clustering
- 4.3 K Means Clustering
- 4.4 Case Study: Identifying news article category from WSJ articles
Module 5: Naïve Bayes, Support Vector Machines & Decision Trees 0/4
- 5.1 Decision Trees
- 5.2 Support Vector Machines(SVM)
- 5.3 Naïve Bayes – Classifier
- 5.4 Case Study: Building a spam classifier
Module 6: Neural Networks & Random Forests 0/4
- 6.1 K Nearest Neighbours
- 6.2 Neural Networks
- 6.3 Case Study: Designing a stock market artificial neural network
- 6.4 Random Forest Classifier
Module 7: Model Performance & Errors 0/6
- 7.1 Model Evaluation Metrics
- 7.2 Confusion Matrix
- 7.3 Adding Complexity & Increase Quality
- 7.4 Training Set & Test Set
- 7.5 Cross Validation
- 7.6 Bias & Variance
Module 8: Recommendation Systems 0/6
- 8.1 Recommendation Systems
- 8.2 Case Study: Designing a Movie Recommendation System
- 8.3 Low Rank Matrix Factorization
- 8.4 User-based Collaborative Filtering
- 8.5 Item-based Collaborative Filtering
- 8.6 Making Recommendations
CVG is the Principal Data Scientist at Hewlett-Packard. An alum of IIM Bangalore, CVG is the faculty for the Machine Learning track. He has an overall experience of 15 years with expertise in Big Data, Predictive Analytics, Statistics, Data Mining, Signal Processing and Algorithm Development in image, video, speech & document processing. He has developed analytical solutions for automotive, IT, healthcare, telecom, travel & transportation industries. He has led more than 30 advanced analytical projects in the last 2 years.
Where do the classes take place?
All the courses are instructor-led and take place online. The online interface lets you and the faculty have a two-way interaction. It’s as good as sitting in a physical classroom.
What’s the benefit of taking online instructor-led courses?
In physical classrooms, students generally feel hesitant to ask questions. If you miss any class or didn’t understand some concepts, you can’t go through the class again. However, in online courses, it’s possible to do that. We share the recordings of all our classes after each class with the student. Also, there’s no hassle of long distance commuting and disrupting your schedule.
Who will be the instructor?
We have some of the top-most faculty for Big Data & Data Science. A typical instructor at UpX Academy, brings with him several years of industrial experience in Big Data and Data Science and comes from prestigious school like ISB, IITs, LBS, etc. You can register for one of our free events to interact with our faculty or also attend a trial class.
When will the classes take place?
All classes take place over the weekends in the mornings. There’ll be one class of 2 to 2.5 hours on Saturdays and Sundays each. This means that you can now acquire in-demand skills without compromising on your schedule.
Do you provide any projects?
Absolutely! We believe that unless you implement the concepts studied in the classes, you are unable to join the dots and hence can’t see the entire picture. Projects let you apply the learned concepts to real-world data sets. We give a number of hands-on exercises, mini case studies and full-blown projects that aid you in doing so.
What kind of projects will I be working on?
You’ll be working on real-time data-sets (which can run in 100s of MBs or possibly in GBs!) which you get to choose from a variety of domains such as retail, finance, social media, healthcare, etc. These data-sets have been curated from top sources such as World Bank, US Health Department, Carnegie Mellon, Stanford and many more.
Where & how will I practice?
You’ll get access to our virtual computing lab through the login credentials provided to you. The virtual machines will enable you to work on “Big Data” sets for your projects and practice hands-on too.
Do I get a certificate of completion or certification?
We provide certification of completion to students who attend at least 70% of the classes. After the course ends, we conduct a certification exam that evaluates them on the skills they have learnt. Certification of Excellence is provided to only those who clear the exam. The exam is purely case-based and not even a single theory question is asked.
Do you provide career assistance?
We provide career workshops and industry immersion sessions to help you become ready for roles you are aspiring for. We also help you in resume review and interview preparation. If you diligently follow our advice, you should start getting interview calls as soon as you finish the course.
Who is the target audience?
Individuals who have a profound inclination for solving business problems by making data-driven decisions.
Can I watch the recordings of the trial sessions before enrolling?
Yes, the recordings of the trial classes are uploaded. Click here to watch a demo class.