Advance Data science is one of the unique courses provided by Netzwerk Academy in this competitive world.
The course is designed to provide a variety of experience to the students from the theoretical classes, practical to placement assistance.
Any graduation is eligible to learn, but the end results of placement affects typically with any specific stream of graduation
Careers to choose after this course:
- Deep learning engineer
- Ai engineer
- DL solution architect
- Jr. Data scientist
- Computer vision engineer
Theoretical classes: Daily 1.5hrs live interactive classes and weekly assessment of assignment and topic specifications.
Practical: Netzwerk Academy is the one and only online training Academy which provides the real-time hands-on experience on premise GPU’s and cloud platforms.
“ focus on the practical knowledge along with theoretical knowledge “ is the key Mantra towards placing our students
With cloud GPU, we provide a chance for every student at Netzwerk Academy to work on the projects at our virtual Artificial Intelligence Labs especially designed for Data scientists to work and build their own projects from scratch with data creation, model building, testing and implementing the end-to-end project.
Simply saying: Whatever the students learn during the sessions, they get a chance to apply that knowledge at out virtual Artificial Intelligence Labs.
- Outbound interviews: A dedicated team of delivery will be working on with referring you to different companies on different employment portals. Student has to apply for the job posts given in the talent pool portal. This team will provide you with several job applications link and portal updates
- Association with employment portals: We have association with several employment portals to access their paid services for our students. The Data analysis with python and Python Development course students will be provided this service at no extra cost. Student can opt any one of the employment portals best to their knowledge.
- Campus placement: This service is exclusive only for Advance Data science course where students who perform really well will be picked in offline workshop itself. Remaining students will get interviews from our Partnered companies.
100% placement guarantee from Netzwerk Academy
There are specific milestones to complete for availing this. After completing them students get assessed by the trainers. The last mock interview will be held by companies itself.
“Know more“(Whats App link)
- Assignment: The most important aspects from student’s point of view to make sure the topics are well prepared, practiced and presented. This gives student a 1-step boost towards building their online presence on GitHub and several other competitive platforms.
Netzwerk academy focuses on preparing students not only in the subject but in their skill development also. Any topic which is covered on a particular day, the student has to explain it to their group mates. Doing so the concepts will be cleared and slowly they will overcome the fear of speaking and will be eventually trained for interviews.
Pricing: Rs. 45000 + GST is the total fees for the course incl. placement assistance
A registration fees if 15% to be paid to book slot and attractive EMI options are provided for the students to accommodate
- What is Artificial Intelligence, Machine Learning and Data Science
- Why is it era of Artificial Intelligence
- Business intelligence v/s Data Science
- Introduction to Python programming language
- Introduction to Machine learning
- Linear Algebra
- Control Flow and Iterations
- In-built Data Structures
- Exception handling
- File handling
- Classes in Python
- Types of data and extraction
- Raw & Processed data
- ED Analysis
- Types of Machine learning :-
- Linear Regression
- Cost Function and Optimization(Gradient Descent)
- Logistic Regression
- Decision Trees
- Model Selection
- Over Fitting & Under Fitting
- Regularization: Ridge and Lasso
- Feature Engineering
- Cross Validation
- Normalization & Standardization
- Hyper Parameter Tuning
- Accuracy Metrics ( Confusion matrix, F1 score, ..)
- Support Vector Machine (SVM)
- Gradient Boosting
- Extreme Gradient Boosting & XG boost
- Artificial Neural Networks
- Introduction to KERAS
- MNIST Dataset
- Convolution Neural Networks(CNN)
- Introduction to Tensorflow & Pytorch
- RNN (Recurrent Neural Networks) and LSTMs
- Convolution Operation and Feature Extraction
- Pooling and types of pooling
- Feature Visualization and CNN layers
- CNN architecture (AlexNet, Inception, ResNet, LeNet)
- YOLO Object Detection
- Image captioning using CNN & RNN
- Robot Localization
- State Transformation
- Vehicle Motion
- GAN (Generative Adversarial Network)
- Project – Custom Object Detection model