Data Science

Our Data Science course makes you master data analysis and AI training, including practical experience with Python libraries, machine learning, and deep learning. With experienced instructors, you'll develop skills to tackle complex data challenges and drive innovation in any industry.

Overview

We offer an exceptional Data Science Program to equip you with the necessary skills for success in today's data-driven world. Our comprehensive program spans over seven months, ensuring a thorough understanding of the data analysis and artificial intelligence (AI) modules.

In the data analysis module, you will dive into the fundamentals of data processing, cleaning, and visualization techniques by Python libraries. You will learn to leverage various statistical methods and tools to extract meaningful insights from complex datasets. You'll gain practical experience in exploring and manipulating data through hands-on projects and real-world examples. This will enable you to make informed decisions and recommendations based on evidence-driven by data.

The AI module will take you on a journey into the exciting world of artificial intelligence. You will explore the principles and algorithms behind machine learning, deep learning, natural language processing (NLP) and computer vision (CV), and learn the working principles of large language models such as ChatGPT and Google Bard. You will acquire the expertise to develop predictive and prescriptive analytics solutions by building and training AI models. From image recognition to language translation, you will discover the limitless possibilities of AI and its transformative impact across industries.

Throughout the program, our experienced instructors with academic degrees will guide you every step of the way. They will provide personalized feedback and support to make your learning journey engaging and rewarding. After the 7-month program, you will become a skilled data scientist with the necessary knowledge. You will have the practical expertise to handle complex data challenges and drive innovation in your field.

Join us today and unlock the vast potential of data science and AI.

Targeted Job Titles

- Data Scientist
- Data Analyst
- Business Analyst
- Data Storyteller
- Database Administrator
- Data Engineer
- Data Architect
- Machine Learning Engineer
- Deep Learning Engineer
- AI Specialist

Courses Curriculum

Data Analysis Module

1.1. IT Fundamentals
1.1.1 Introduction to IT
1.1.2. Hardware Basics
1.1.3. Software Basics
1.1.4. Network Basics
1.1.5. Programming Basics
1.2. Python Programming Language-Core Python
1.2.1. Data Types
1.2.1.1. Python Intro-Installation-Data Types General-PEP-8 Rules
1.2.1.2. String Operations-1 (Indexing, slicing, other methods )
1.2.1.3. String Operations-2 (Formatting and other methods)
1.2.1.4. Boolean Types(logical, Artimetic, Assignment Operators and other operators
1.2.1.5. List and List methods
1.2.1.6. Tuples and Sets
1.2.1.7. Dictionaries
1.2.2. Key Topics
1.1.2.1. If-Elif-Else-Catch
1.1.2.2. While and For loops
1.1.2.3. Functions
1.3. Python Programming Language-Advanced Python
1.3.1 Try Exceptions
1.3.1.1. OOP
1.3.1.2. File_Handling
1.3.1.3. Random and Json module
1.3.1.4. Datetime and Regex
1.4. Git-Github
1.5. SDLC-Jira
1.6. HTML+CSS
1.7. SQL
1.8. Google SpreadSheets (GSS)
1.9. Numpy-Pandas
1.10. Statistics
1.11. Data Visualization (Matplotlib, Seaborn, Plotly, Bokeh)
1.12. Tableau
1.13. Power BI
1.14. Data Storytelling
1.15. Capstone Projects (5 Projects)

Artificial Intelligence (AI) Module

2.1. Machine Learning
2.1.1. Supervised Learning
2.1.1.1. Naive Bayes
2.1.1.2. Linear Regression
2.1.1.3. Logistic Regression
2.1.1.4. Support Vector Machines (SVM)
2.1.1.5. K-Nearest Neighbor (KNN)
2.1.1.6. Decision Tree
2.1.1.7. Random Forest
2.1.1.8. Boosting Methods (BM)
2.1.1.8.1. Ada Boosting Methods (ABM)
2.1.1.8.2. Gradient Boosting Methods (GBM)
2.1.1.8.3. XGBoosting Methods (XGBM)
2.1.2. Unsupervised Learning
2.1.2.1. K-Means Clustering
2.1.2.2. Hierarchical Clustering
2.1.2.3. Principal Component Analysis (PCA)
2.1.3. Recommender Systems
2.2. Deep Learning
2.2.1. Artificial Neural Networks (ANN)
2.2.2. Convolutional Neural Networks (CNN)
2.2.3. Computer Vision
2.2.4. Recurrent Neural Networks (RNN)
2.2.4.1. Long Short-Term Memory (LSTM)
2.2.4.2. Gated Recurrent Unit (GRU)
2.2.5. Natural Language Processing (NLP)
2.3. Web Scraping
2.4. Prompt Engineering
2.5. Deployment
2.5.1. Streamlit
2.5.2. Flask
2.5.3. AWS-Docker
2.5.4. Heroku
2.5.5. Capstone Projects (15 Projects)
3. Career Coaching
4. Internship Project

Announcement

Are you ready to enter the extraordinary world of Data Science and Artificial Intelligence? Prepare for an exceptional journey with TechPro Education’s groundbreaking bootcamp designed to set you apart from your competitors.

What makes us different, you ask? Get ready to be amazed! We offer a comprehensive Data Science programme that goes beyond the ordinary. Get ready to dive deep into cutting-edge technologies and open the doors to the mysterious world of data.

Here's what makes our Data Science programme stand out from the rest:

60 hours of intensive Computer Vision training: Master the art of extracting meaningful insights from visual data, unravelling patterns and trends the naked eye can't see.

All training with Chat GPT integration: Experience the power of AI as our curriculum seamlessly integrates with Chat GPT, allowing you to explore innovative approaches and leverage the latest advancements in Natural Language Processing.

Data Storytelling training: Learn to transform complex data into compelling narratives that captivate audiences and drive informed decision-making.

Prompt Engineering: Unleash your creativity with advanced Prompt Engineering techniques, enabling you to generate precise and context-aware model responses.

More than 20 Capstone Projects: Apply your skills to real-world challenges through our extensive collection of Capstone Projects, gaining hands-on experience and building an impressive portfolio.

Internship opportunities in Europe and America: Broaden your horizons and gain global exposure through our exclusive internship placements in renowned companies across Europe and America.

University certificate from Richmond College, UK: Stand out with an accredited university certificate, validating your expertise and opening doors to limitless opportunities.

Internship opportunity with academics from Stanford University in Silicon Valley: Immerse yourself in the epicentre of innovation, working alongside esteemed scholars from Stanford University in a Silicon Valley company.

Opportunity to start to work four months after starting the course: Fast-track your career with the option to secure employment just four months into the program, showcasing your competence and accelerating your professional growth.

Personalized career coaching: Receive expert guidance and support with resume and CV preparation, one-on-one job search assistance, and invaluable interview coaching.

Training for professional social platforms: Learn the art of building a solid professional presence through tailored training on leading social media.

Academic mentoring and study groups: Foster personal growth through dedicated academic mentoring and collaborative study groups, creating a supportive learning environment.

Mock interviews: Hone your interview skills and boost your confidence with mock interview sessions, preparing you to shine in any professional setting.

Take advantage of this extraordinary chance to become a trailblazer in the field of Data Science. Secure your spot today and unlock a successful and fulfilling career.

Schedule

Turkish Course Night Time Schedule

Day	EST	CET	TSI
Monday	01:30 pm - 04:30 pm	19:30 - 22:30	20:30 - 23:30
Tuesday	01:30 pm - 04:30 pm	19:30 - 22:30	20:30 - 23:30
Wednesday	01:30 pm - 04:30 pm	19:30 - 22:30	20:30 - 23:30
Thursday	01:30 pm - 04:30 pm	19:30 - 22:30	20:30 - 23:30
Friday	01:30 pm - 04:30 pm	19:30 - 22:30	20:30 - 23:30
Saturday	01:30 pm - 04:30 pm	19:30 - 22:30	20:30 - 23:30
Sunday	-	-	-

EST : Eastern Standard Time
CET : Central European Time
TSI : Turkish Time

Note: Please note that schedules may change due to daylight saving time in summer and winter.

FAQ

Do you need a Maths background to be a Data Scientist?

No, it is not necessary. Basic knowledge of Mathematics at the high school level is sufficient. Although machine learning algorithms have a mathematical background, it is not required to master these mathematical topics to use these algorithms. However, you may need to lean on these topics if you want to do academic work or deepen the mathematical dimension. Apart from that, you do not need an advanced knowledge of mathematics to work as a data scientist, data analyst, and similar positions in the sector. The primary statistical concepts necessary to grasp machine learning topics will be taught in our course.