Data Scientist
in 4 Months
Looking to land a Job in Data Science?
At Code Kaisen, we’ll give you the skills, 1-on-1 mentorship and help you build the required portfolio with real-world projects to make it happen. Book a free session to start your Data Science journey today!
- Student Satisfaction Guarantee
- Practical Intensive Session
- Career Guidance
- Affordable Price
Data Scientist
in 4 Months
Looking to land a Job in Data Science?
At Code Kaisen, we’ll give you the skills, 1-on-1 mentorship and help you build the required portfolio with real-world projects to make it happen. Book a free session to start your Data Science journey today!
- Student Satisfaction Guarantee
- Practical Intensive Session
- Career Guidance
- Affordable Price
Test Your Analytical Mindset
Begin Your Journey in Data Science with the Free Data Science PlayBook. This guide is crafted to be accessible and informative for all levels, offering a clear path from foundational concepts to advanced topics like AI. Seize the opportunity to transform your understanding of data. Obtain your PlayBook today and embark on an enlightening path in the data science realm.
Features Include:
- Educational guide
- Self-Assessment Tools
- Interactive Exercises
- Real World Applications
- Beginner's Learning Pathway
Project Showcases
Weather Condition Classification
Dry Bean Classification
Multifaceted Predictive Analytics
Program Curriculums
Overview of Python:
– Introduction to Python as a versatile programming language.
– Applications in Data Science, machine learning, web development, and more.
– Comparison with other programming languages in terms of readability and community support.
Setting Up the Environment:
– Overview of Google Colab as an online Python development platform.
– How to use Colab notebooks for Python coding, including integration with Google Drive for data storage and sharing.
Python Syntax and Program Flow:
– Writing and understanding Python syntax.
– Print statements and debugging techniques.
Basic Programming Concepts:
– Variables and data types: integers, floats, strings, booleans.
– Type casting and user input handling.
– Operators: arithmetic, comparison, logical, and assignment.
Writing Your First Python Program:
– Combining basic concepts into a simple Python program.
Built-in Functions:
– Introduction to commonly used Python built-in functions.
String Operations:
– String creation, concatenation, slicing, and indexing.
– Common string methods such as `upper()`, `lower()`, `find()`, `replace()`, and more.
– Understanding the difference between functions and methods.
Introduction to Libraries:
– Overview of essential libraries used in Data Science: NumPy, Pandas, and Matplotlib.
Basic Data Handling:
– Reading and writing data files (CSV, Excel).
– Performing basic data operations: sorting, filtering, and summarizing.
Exploring Datasets:
– Initial data exploration and simple analysis techniques.
Conditional Statements:
– Using `if`, `elif`, and `else` statements.
– Understanding the importance of indentation in Python.
Nested Conditionals:
– Writing and understanding nested conditional statements.
Using Conditional Statements on Data:
– Applying conditional statements to filter and manipulate data effectively.
Lists:
– Creating, indexing, slicing, and performing operations on lists.
– List methods: `append()`, `remove()`, `sort()`, and more.
– Comparing lists with arrays.
Tuples:
– Understanding the characteristics and applications of tuples.
Dictionaries:
– Creating, accessing, and modifying dictionaries.
Creating Artificial Data:
– Using basic data structures to create artificial data.
Using Multiple Libraries Together:
– Integrating NumPy, Pandas, and Matplotlib for data manipulation and visualization.
Custom Functions:
– Defining functions, using arguments, and returning values.
– Applying custom functions on datasets.
Advanced Data Operations:
– Data cleaning and preprocessing techniques.
– Applying custom functions on datasets for advanced data handling.
Loops:
– Writing `for` loops and `while` loops for repetitive tasks.
– Understanding and applying nested loops.
Integrating Loops with Data Handling:
– Using loops for data manipulation and handling.
Hands-on Project:
– Applying learned concepts on a real dataset.
– Step-by-step project implementation, from data handling to analysis.
Debugging and Troubleshooting:
– Identifying and fixing common issues in Python code.
Presentation of Project Findings:
– Sharing results and insights from the hands-on project.
Q&A and Review Session:
– Reinforcing key concepts and addressing any remaining questions.
Data Science Explained: Exploring the fundamental concepts and applications of Data Science.
Importance of Data in Decision Making: Discussing how data influences business and organizational decisions.
Data Related Roles and Responsibilities: Understanding the variety of roles in the data science field.
Skillset Required for Data Science: Reviewing the essential skills needed for a career in Data Science.
Data Science Overview: Providing a general overview of the Data Science field.
Understanding Business Objectives: Grasping the goals and objectives in data science projects.
Problem Identification: Identifying and defining problems to be solved by data science.
Defining Success Metrics: Establishing criteria for success in data science initiatives.
Scope Definition: Outlining the boundaries and scope of data science projects.
Data Understanding & Availability: Assessing the availability and comprehension of necessary data.
Feasibility Study: Conducting studies to evaluate the practicality of the project.
Formulating Hypotheses: Developing hypotheses for data-driven investigation.
Project Planning: Effectively planning and structuring data science projects.
Understanding Data Needs: Recognizing the specific data requirements for a project.
Data Sources Identification: Identifying potential sources of data.
Data Acquisition Methods: Learning about different methods for collecting data.
Data Formats and Storage: Understanding various data formats and storage options.
Data Quality Assessment: Evaluating the quality of collected data.
Data Cleaning and Preprocessing: Preparing data for analysis through cleaning and preprocessing.
The Data Analysis Process: Delving into the step-by-step process of data analysis.
Types of Data Analysis: Exploring different methodologies in data analysis.
Exploratory Data Analysis: Conducting preliminary analysis to understand data patterns.
Statistical Analysis Fundamentals: Understanding basic statistical methods in data analysis.
Data Visualization: Using visual tools to represent data for easier comprehension.
Introduction to Machine Learning: Exploring the basics of machine learning.
Model Selection and Evaluation: Learning how to select and assess the performance of models.
Supervised and Unsupervised Learning: Discussing two primary types of machine learning.
Feature Engineering and Selection: Understanding the importance of feature selection in modeling.
Data Preprocessing for Machine Learning: Preparing data specifically for machine learning applications.
Overfitting and Underfitting: Learning about common pitfalls in model training.
Model Training: Delving into the process of training data models.
Ensemble Methods: Exploring advanced techniques in machine learning.
Understanding Your Audience: Tailoring data communication to different audiences.
Data Storytelling: Mastering the art of narrating data-driven stories.
Principles of Effective Data Visualization: Learning key principles for effective data visualization.
Writing Effective Reports and Presentations: Developing skills for creating impactful reports and presentations.
Interactive Data Tools and Dashboards: Utilizing tools for interactive data analysis and presentation.
Continuous Improvement – The ‘Kaisen’ Strategy: Embracing ongoing improvement in data science practices.
Project Selection and Proposal: Choosing and outlining a project that showcases data science skills and interests.
Project Methodology: Implementing a comprehensive approach that includes gathering and analyzing data, and developing and validating models for accuracy.
Project Deliverables: Presenting results with a well-crafted narrative and effective data visualization.
Feedback and Peer Review: Participating in constructive feedback sessions and peer reviews.
Reflection on Learning: Reflecting on the learning journey and skills developed throughout the course.
Meet Your Instructor
I’m an explorer, researcher, and dedicated educator deeply passionate about Data Science. My journey started with teaching mathematics and Python, leading me into the captivating realm of data. Discovering its potential for solving complex problems brought me immense joy.
My teaching began in high school, igniting a lifelong commitment to sharing knowledge. I hold a bachelor’s degree in computer science, with over 1,500 hours of teaching experience and certifications in data analysis, coding, and AI. I have taught nearly 100 students and have provided my guidance and expertize in 500+ student projects, assignments, and theses. I offer structured guidance, saving students valuable time.
My teaching methodology emphasizes structured learning, practical application, and interactive sessions. I simplify complex topics, integrate hands-on projects, and prioritize student engagement. With personalized attention, I ensure effective progress and real-world relevance.
Teaching isn’t just a profession; it’s my passion. In every class, I aim to inspire the same enthusiasm for Data Science that drives me. From demystifying data to exploring AI, join me in making learning both enjoyable and enlightening.
Let’s explore Data Science together!
Have Questions To Ask?
Schedule a personal consultation with Ahmed to discuss your learning goals, program details, or any queries you have. Your data science journey is unique, and we're here to guide you!
Schedule An AppointmentI’m an explorer, researcher, and dedicated educator deeply passionate about Data Science. My journey started with teaching mathematics and Python, leading me into the captivating realm of data. Discovering its potential for solving complex problems brought me immense joy.
My teaching began in high school, igniting a lifelong commitment to sharing knowledge. I hold a bachelor’s degree in computer science, with over 1,500 hours of teaching experience and certifications in data analysis, coding, and AI. I have taught nearly 100 students and have provided my guidance and expertize in 500+ student projects, assignments, and theses. I offer structured guidance, saving students valuable time.
My teaching methodology emphasizes structured learning, practical application, and interactive sessions. I simplify complex topics, integrate hands-on projects, and prioritize student engagement. With personalized attention, I ensure effective progress and real-world relevance.
Teaching isn’t just a profession; it’s my passion. In every class, I aim to inspire the same enthusiasm for Data Science that drives me. From demystifying data to exploring AI, join me in making learning both enjoyable and enlightening.
Let’s explore Data Science together!
Have Questions To Ask?
Schedule a personal consultation with Ahmed to discuss your learning goals, program details, or any queries you have. Your data science journey is unique, and we're here to guide you!
Schedule An AppointmentMuhammad Ahmed has provided a really well tailored and engaging educational experience. He is very good at articulating the learning points in an easy to understand way and plans lessons around practical examples to make the learning material relatable and engaging. He has helped with work related problems on top of going through his planned lessons and I have really appreciated his flexibility given my work and childcare commitments.
Tom
It is always a pleasure to have a class with him, because of the tailoring he puts into each session. He made a conscious effort to provide the exercises I needed at the skill level I had attained by the start of the class. He is also great at providing a good sense of progression as well as ensuring there is a solid foundation before moving to the next thing.
Christian
Muhammad is an incredible tutor! He is very organized, patient and explains even the most difficult of concepts very well. He really goes above and beyond in preparing for every session to make sure your time is well spent. He truly has a gift for teaching. I look forward to continuing my sessions with him. Muhammad is one of the best tutors I have had; if you choose to try tutoring with Muhammad, you will not regret it.
Irie
If you need someone to help you get more comfortable with Python, Ahmed is the person to turn to. You’ll work on your your areas of weakness until they become strengths, you’ll understand how to solve Python problems of increasing difficulty, and you'll gain the skills you need to approach problems from multiple angles. Ahmed is friendly, easygoing, and great at explaining new concepts.
Sasha
I love working with Muhammad Ahmed. I can be at times slower in understanding/ revising new analytics concepts, and Muhammad has demonstrated a lot of patience in going through complex features slowly and with humility. I absolutely would recommend him to any student of data science as he is one of the most enthusiastic and helpful teachers I have had. He will adjust his course based on a student's needs and enthusiastically support each student through the hurdles they face. I wholeheartedly recommend him for tutoring data science.
Saeb
Classes with Ahmed was a lifetime experience for me. I have never met one person so patient and dedicated to his work. Very intelligent, empathetic tutor, which put all his time and effort for you to understand, learn and suceed. He helped me to overcome the biggest challenge as a student so far. I am absolutely sure, anyone who choose to work with him, will be able to achieve the best results. Thank you for everything and all the best in the future 🙏🏻⭐️
Karolina
Muhammad Ahmed has provided a really well tailored and engaging educational experience. He is very good at articulating the learning points in an easy to understand way and plans lessons around practical examples to make the learning material relatable and engaging. He has helped with work related problems on top of going through his planned lessons and I have really appreciated his flexibility given my work and childcare commitments.
Tom
It is always a pleasure to have a class with him, because of the tailoring he puts into each session. He made a conscious effort to provide the exercises I needed at the skill level I had attained by the start of the class. He is also great at providing a good sense of progression as well as ensuring there is a solid foundation before moving to the next thing.
Christian
Muhammad is an incredible tutor! He is very organized, patient and explains even the most difficult of concepts very well. He really goes above and beyond in preparing for every session to make sure your time is well spent. He truly has a gift for teaching. I look forward to continuing my sessions with him. Muhammad is one of the best tutors I have had; if you choose to try tutoring with Muhammad, you will not regret it.
Irie
If you need someone to help you get more comfortable with Python, Ahmed is the person to turn to. You’ll work on your your areas of weakness until they become strengths, you’ll understand how to solve Python problems of increasing difficulty, and you'll gain the skills you need to approach problems from multiple angles. Ahmed is friendly, easygoing, and great at explaining new concepts.
Sasha
I love working with Muhammad Ahmed. I can be at times slower in understanding/ revising new analytics concepts, and Muhammad has demonstrated a lot of patience in going through complex features slowly and with humility. I absolutely would recommend him to any student of data science as he is one of the most enthusiastic and helpful teachers I have had. He will adjust his course based on a student's needs and enthusiastically support each student through the hurdles they face. I wholeheartedly recommend him for tutoring data science.
Saeb
Classes with Ahmed was a lifetime experience for me. I have never met one person so patient and dedicated to his work. Very intelligent, empathetic tutor, which put all his time and effort for you to understand, learn and suceed. He helped me to overcome the biggest challenge as a student so far. I am absolutely sure, anyone who choose to work with him, will be able to achieve the best results. Thank you for everything and all the best in the future 🙏🏻⭐️
Karolina
Pricing
Python For Data Science
3 Weeks Program- Domain Specific Programming Focus
- Hands On Python Training
- Multifaceted Learning Experience
- On Demand Recordings
- Expert Mentorship
- AI Integrated Learning
Data Science Comprehensive
3 Months Program- Comprehensive Curriculum
- Practical Hands On Learning
- Group Interactive Sessions
- Continuous Assessment
- One on One Mentorship
- Guided Portfolio Project
- On Demand Recordings
- Certificate of Completion
Data Science
1 on 1
Self Paced
- Comprehensive Curriculum
- Practical Hands On Learning
- Study at own Convenience
- One on One Interactive Sessions
- Continuous Assessment
- Expert Mentorship
- Guided Portfolio Project
- On Demand Recordings
- Certificate of Completion
Python For Data Science
3 Weeks Program- Domain Specific Programming Focus
- Hands On Python Training
- Multifaceted Learning Experience
- On Demand Recordings
- Expert Mentorship
- AI Integrated Learning
Data Science Comprehensive
3 Months Program- Comprehensive Curriculum
- Practical Hands On Learning
- Group Interactive Sessions
- Continuous Assessment
- One on One Mentorship
- Guided Portfolio Project
- On Demand Recordings
- Certificate of Completion
Data Science
1 on 1
Self Paced
- Comprehensive Curriculum
- Practical Hands On Learning
- Study at own Convenience
- One on One Interactive Sessions
- Continuous Assessment
- Expert Mentorship
- Guided Portfolio Project
- On Demand Recordings
- Certificate of Completion
Frequently Asked Questions
Our bootcamps are ideal for anyone looking to build or enhance their skills in coding and data science, from beginners to those with some experience. A passion for learning and a commitment to engagement in the course material are essential.
Prior experience is not mandatory. Our “Python For Data Science” bootcamp is designed to accommodate beginners, while our “Data Science Comprehensive” bootcamp suits both beginners and those with some coding background.
Expect a mix of theoretical learning and practical application, with a strong emphasis on interactive and hands-on experiences. Classes are designed to be engaging, with real-world problem-solving and project work.
Yes, upon successful completion of any of our bootcamps, you will receive a Certificate of Achievement, which recognizes your skills and dedication to learning.
Bootcamps consist of weekly modules that include interactive sessions, project work, and self-study components. We strive to balance intensive learning with manageable workloads.
In our bootcamps, you’ll engage in a variety of projects ranging from practical coding challenges to comprehensive data analysis tasks. These projects are designed to simulate real-world scenarios, allowing you to apply the concepts you learn in a practical setting. This hands-on approach not only solidifies your understanding of the material but also helps you build a portfolio of work that demonstrates your skills to potential employers.
Many of our students successfully balance the bootcamps with full-time employment. We recommend planning your schedule to accommodate the course workload.
We are open to providing financial aid to those who are in need. You can book a call with us to discuss the details and see if you are eligible for a financial aid.