Course Overview:

The Accelerated Data Science and Machine Learning Bootcamp is an immersive and comprehensive training program designed to equip participants with the essential skills and knowledge needed to excel in the dynamic field of data science. Through a blend of theory, hands-on projects, and real-world applications, participants will learn how to extract valuable insights from data, build predictive models, and make data-driven decisions across various industries. This intensive bootcamp covers a wide range of topics, from data wrangling and statistical analysis to machine learning and data visualization, preparing participants to become proficient data scientists and analysts.

Learning Outcomes:

• Data Exploration and Analysis: Participants will be able to perform exploratory data analysis (EDA) using various data visualization techniques and statistical methods to gain insights, identify patterns, and draw meaningful conclusions from complex datasets.

• Machine Learning Proficiency: Participants will acquire a solid foundation in machine learning algorithms, enabling them to build and evaluate predictive models for regression, classification, and clustering tasks.

• Data Wrangling and Pre-processing: Participants will develop the skills to acquire, clean, and preprocess raw data, addressing missing values, outliers, and inconsistencies, to ensure data quality and suitability for analysis.

• Feature Engineering and Selection: Participants will learn how to select and engineer relevant features from data, optimizing model performance and enhancing the predictive capabilities of machine learning models.

• Real-World Project Experience: Through hands-on projects and case studies, participants will gain practical experience in applying data science techniques to real-world datasets and business scenarios, preparing them for real-life data challenges.

• Data Visualization and Communication: Participants will be able to create compelling data visualizations that effectively communicate insights and findings to non-technical stakeholders, facilitating data-driven decision-making.

• Ethical Considerations in Data Science: Participants will be aware of the ethical implications and potential biases in data science projects, understanding the importance of responsible and unbiased data analysis and decision-making.

Course Outline

Instructor

Shazeb Ali

MBA Tech Management - James Madison University, USA
BS Information System - George Mason University, USA
Head of Data Analytics - Syntax Technologies, USA
Instructor at Enterprise Business Solutions, Thinkful and Datacamp.com

Application Process:

Participants must register online through the CES website by clicking on their desired course and filling out a one-page form. Before starting the registration process, please ensure that you have the following:

- A passport-sized photograph for the CES smartcard. It should be against a white background.

- Correct CNIC details.

Incorrect information provided during the registration process will lead towards cancellation of your enrolment at any stage, and participants will not be entitled to claim a refund.

Once you have completed your online registration, you may proceed to the payment section. You have two options:

1. Pay online using your bank debit/credit cards through LUMS online payment system https://pay.lums.edu.pk

2. Download the fee voucher and deposit cash in any branch of the designated banks specified on the fee voucher.

Once the payment has been made, you will receive a confirmation email within 24 to 48 working hours, and your payment status will be updated to "ENROLLED" in the online application portal.

Installment:

KalPay Taleem offers an instalment facility for participants enrolled in CES on-campus courses and workshops. If you want this option, please email taleem@kalpayfinancials.com or call at 0328 3044414??for more information.

Note: CES may cancel or postpone a course due to insufficient enrolment or unforeseen circumstances. In this case, the university will refund registration/processing fee (if any) but will not be responsible for any other related charges/expenses including cancellation/change charges by airline and travel agencies.

Please go through Policies & Code of Conduct