Advance Data Science
| Duration : | 5 Months |
|---|---|
| Mode : | Online Live Classes |
| Placement : | Assistance & Guarantee |
| Language : | English |
| EMI : | Available |
About
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.
Eligibility
Any graduation is eligible to learn, but the end results of placement affects typically with any specific stream of graduation
Course Highlights
1. Everyday session will be scheduled after 6pm (between 6pm to 9pm).
2. Each day session will be of 60mins to 90mins based on topic.
3. Sessions will be live and lead by teachers.
4. No recordings will be provided.
Careers to choose after this course
- Deep learning engineer
- Ai engineer
- DL solution architect
- Jr. Data scientist
- Computer vision engineer
What’s Unique
PRESENTATIONS
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.
ASSIGNMENTS
Every student gets a fixed number of assignments which are spread evenly in all topics. By completing the assignments they gain an in-depth knowledge of the subjects and side by side there Github library gets built. Every time they give an interview, the very next thing after their resume is the Github link to their library.
PRACTICAL
We at Netzwerk Academy focus on the practical knowledge more than theoretical knowledge. Netzwerk Academy is the only institute in India which provides Practical Implementation at offline workshops. Whatever the students learn during the sessions, they get a chance to apply that knowledge at out Artificial Intelligence Labs.
CERTIFICATION
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.
Placement Assistance
- 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
- Employment portal optimization will be taught to fetch you the interviews (Naukri.com, LinkedIn +3 other portals)
Fees
Rs. 45000 + 18% GST = Rs. 53,100 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
- Statistics
- Probability
- Linear Algebra
- Calculus
- Basics
- Control Flow and Iterations
- In-built Data Structures
- Functions
- Exception handling
- File handling
- Classes in Python
- Numpy
- Matplotlib
- Pandas
- Introduction
- Types of data and extraction
- Raw & Processed data
- ED Analysis
- Types of Machine learning :-
- Supervised
- Regression
- Classification
- Unsupervised
- Clustering
- Linear Regression
- Cost Function and Optimization(Gradient Descent)
- Logistic Regression
- KNN
- 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
- Supervised
- Introduction
- Artificial Neural Networks
- Introduction to KERAS
- MNIST Dataset
- Convolution Neural Networks(CNN)
- Introduction to Tensorflow & Pytorch
- RNN (Recurrent Neural Networks) and LSTMs
- OpenCV
- 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
- Motion
- Robot Localization
- State Transformation
- Vehicle Motion
- Autoencoders
- GAN (Generative Adversarial Network)
- Project – Custom Object Detection model
Projects
Smart doorbell camera
Face recognition model for both still images and video streams is built using python, OpenCV and deep learning model. This model helps to detect the facial pattern and to identify that person based on the model trained. This can be deployed on Jetson board to build a smart doorbell camera system.
Speech Recognition
Speech recognition model is used to recognize the speech and convert it to desired form. The speech is recognized and is converted to digital form which can be used as input to build a model. Speech to speech, speech to text models are developed using CNN algorithm, python as tool. The applications of speech recognition are Apple Siri, Amazon’s Alexa, Google translator, etc.
Object Detection
Object detection is an emerging technology where instances of various objects are detected, to build this model, computer vision and image processing concepts are used. Object detection is proving to be revolutionary in the development of Self driving cars. The picture classification can also be done using this model.
