Fawad has over 10+ years of experience in helping organizations make data driven decisions using machine learning and big data. With distinction in Strategy and Big Data, Fawad has helped 1000s of students and industry professionals break into the world of Data Science.
Hadi is the cofounder of Data Science Journey, a platform aiming to help students and entrepreneurs break into data science careers. He also is the founder of Liquid Technologies, a company that is focused towards providing cutting edge Data Analytics and Software Development services to our clients.
Junaid Haris is a Machine Learning Engineer with passion for teaching and empowering the youth of Pakistan. He is an Instructor with Fawad and Hadi at Data Science Journey.
Python is one of the most popular languages and is gaining a lot of popularity in the machine world domain. It is not only easy to learn but allows users a lot of flexibility to design different projects. This unit will teach you about the application of data science and machine learning in python. The course is designed such that even students with no programming background will be able to learn the fundamental concepts. The scope will only be based on concepts which is needed in the real world. We will focus on the following topics ● Python fundamentals ● Variables, data types & comparison operators ● Logical operators ● Loops and functions ● Lists and list comprehensions ● Dictionaries ● Lambdas functions ● Maps and filters ● Data distributions ● Scatter plots ● Displaying and describing quantitative data ● Dealing with different data types in Python. Libraries to be covered ● Pandas ● Numpy ● Matplotlib ● Scikit learn ● Seaborn Learning outcomes ● Become familiar with Python and its applications in data science ● Ability to code machine learning algorithms using built-in libraries ● Perform advanced data wrangling using python commands and libraries ● Ability to create custom functions that help in automating ML pipelines. ● Perform data exploration and impute missing values in a data frame
Power BI is a business analytics service by Microsoft. It aims to provide interactive visualizations and business intelligence capabilities with an interface simple enough for end users to create their own reports and dashboards. In this course, you will learn how to connect, explore, and visualize data with Power BI. Power BI Desktop provides a free-form canvas for drag-and-drop data exploration as well as an extensive library of interactive visualizations, simple report creation, and fast publishing to the Power BI service. Topics: Introduction to Business Intelligence and Data Analysis and Visualization Introduction to Power BI Connection to different data storages Data Modelling in Power BI a) Relationships in Power BI b) Quick Measures and Calculated Measures in Power BI c) Calculated Tables and Calculated Columns d) Time Intelligence Visuals in Power BI a) Create and Format Visualization b) Analytics Pane c) Clustering Data d) Slicers e) Map Visualization f) Tables and Matrixes g) Waterfall Chart, Funnel chart, and Scatter Chart h) Gauge, cards, and KPIs i) Visual Interactions j) Positioning, aligning, and sorting visuals Dashboard and Power Bi Services
Machine Learning is a fundamental aspect of data analytics that automates analytical model building in modern business. In the big data era, managers are able to use very large and rich data sources and to make business decision based on quantitative data analysis. Machine Learning covers a range of state-of-the-art methods/algorithms that iteratively learn from data, allowing computers to find hidden patterns and relationships in such data so as to support business decision. Emphasis is placed on applications involving the analysis of business data. Students will practice applying machine learning algorithms to real world datasets by using an appropriate computing package in Python. The classes will contain a training session and a LAB session to demonstrate the theory into practice. Learning unit outcome On successful completion of this course, you should be able to: ● Have a deep understanding on different types of learning algorithms and can identify advantages and limitations of each method ● Build a strong machine learning skill set for business decision making ● Create machine learning models for studying relationship amongst business variables ● Work with various data sets and identify problems within real-world constraints ● Demonstrate proficiency in the use of statistical software, e.g. Python, for machine learning models implementation. This unit introduces modern machine learning techniques and builds skills in using data for everyday business decision making. Topics include: 1) Machine Learning Foundation; 2) Modern Regression Methods a. Linear regression b. Ridge c. Lasso d. Elastic net 3) Advanced Classification Techniques a. Logistic regression; b. Decision trees 4) Ensemble algorithms; a. AdaBoosting b. Random Forest 5) KNNs a. Regression b. Classification 6) Unsupervised learning a. Kmeans clustering Techniques we will be covering ● Model selection ● Addressing Class-imbalance ● Regularization ● Hyper-parameter selection and tuning ● Cross validation ● Train, validation and test set
Detailed workshops on tricks and tips on different feature engineering and feature selection techniques along with a full ML project on HR ANALYTICS
You will not listen to one-way lectures, rather be in a digital classroom with some of the best experts and class fellows. Class size won’t be massive and you’ll have the floor to yourself to ask questions, debate, share your thoughts and contribute to everyone’s mastery.
Coursework like pop quizzes, short assignments, case studies can really help refresh and reinforce concepts. When everyone’s participating and sharing their ideas, you’ll feel challenged to come up with bigger and better ideas, thus having work to show by the end of the cohort.
Teamwork makes the dream work. Connect with your classmates, a group of like-minded people working towards the same goals and course outcomes as you. Support, challenge yourself and others, and possibly build lifelong relationships.
Live, cohort-based courses are all about the transformation over a short period of time. This is what you and your cohort work together to achieve. You will come out of this course transformed in many, many ways.
This is not an ordinary course but a masterclass specially designed to help you become successful in the market. Some of the perks include:
All the classes will be conducted live giving you the opportunity to engage with the instructor and fellow course takers.
If for some reason, you missed a lecture, videos will be provided for you to stay up to speed with the class.
Meet Successful people who started their journey from content creation. Seek inspiration and learn from their experiences.
Clearly designed assignments and goals to build your foundations throughout the class
A Dedicated Slack community to connect with your classmates and instructor
Get inspiration from the work of your fellows. Find your own tribe of supporters!
The class will have batches in Local language.
Certification will be provided to participants.
Apply now and get free access to the precourse work.