Data Science with Deep Learning

3 out of 5
6 reviews

Our Data Science with Deep Learning course is designed to equip you with the skills and knowledge to harness the power of deep learning in solving complex data problems. Whether you’re a beginner or have some experience in data science, this course will take you on a transformative journey to master the intersection of data science and deep learning.

In this course, you’ll dive into the fundamentals of data science, exploring key concepts such as data pre processing, feature engineering, and model evaluation. You’ll learn how to manipulate and prepare data for deep learning models, ensuring you have a solid foundation for advanced analysis.

Next, we’ll delve into the world of deep learning, covering essential concepts like neural networks, convolutional neural networks (CNNs), recurrent neural networks (RNNs), and deep reinforcement learning. Through hands-on exercises and projects, you’ll gain practical experience in building, training, and fine-tuning deep learning models.

We’ll explore popular deep learning frameworks like TensorFlow and PyTorch, providing you with the necessary skills to implement complex algorithms and architectures. You’ll learn how to leverage pre-trained models and apply transfer learning techniques to accelerate your deep learning projects.

Throughout the course, we’ll emphasize the real-world applications of deep learning in various fields. From image and speech recognition to natural language processing and recommendation systems, you’ll discover how deep learning is revolutionizing industries and driving innovation.

With deep learning skills, you can pursue roles like data scientist, machine learning engineer, AI researcher, or deep learning specialist. These roles are in high demand and offer lucrative career prospects as organizations strive to extract valuable insights from complex data.

Enroll now in our Data Science with Deep Learning course and embark on a transformative journey to become a proficient data scientist equipped with powerful deep learning skills. 

Join us today and take the first step towards mastering data science with deep learning!

Introduction to Data Science

Python Programming

Object Oriented Programming

SQL & Advanced SQL



Machine Learning Part - 1

Machine Learning Part - 2

Data Visualization

Introduction to Neural Networks

Optimization Algorithm

How to build Nueral Netwrok from scratch

Deep learning Tensorflow 2.0

Introduction to Deep NN

Deep learning Over fitting

Deep learning Initialization

Gradient descent & learning rate schedules


Case Study

Data Science involves the analysis of large datasets using coding and statistics to find patterns in this data. Computer Science, on the other hand, involves using logic to write codes that will help complete tasks of varied levels of complexity.
Even if you think you have previously struggled with mathematics, you can still master the data science math abilities. No doubt , data science requires an understanding of math, but the necessary data science math skills can be learned.
The main job of Data Scientists is to analyze large amounts of data using artificial intelligence and statistics to make sense of it and to find patterns in this data, to be able to apply the derived knowledge in solving real-world problems.
Python is the most commonly used programming language for deep learning with popular libraries such as TensorFlow, Keras, PyTorch, and MXNet.
Some examples of application of deep learning include image-based medical diagnosis, fraud detection in financial transactions, self-driving systems, and personalized marketing.
Enrolled: 34 students
Duration: 162 Hours
Level: Advanced

Working hours

Monday 9:30 am - 7.30 pm
Tuesday 9:30 am - 7.30 pm
Wednesday 9:30 am - 7.30 pm
Thursday 9:30 am - 7.30 pm
Friday 9:30 am - 7.30 pm
Saturday 10:00 am - 7.00 pm
Sunday 10:00 am - 7.00 pm