Data Science: Advanced Course
The AEC Data Science-Advanced certification exam validates your readiness for a career in the Data Science industry. The exam assesses your proficiency in all aspects of Data Science. As a Data Science professional, you are expected to possess an extensive understanding of SQL, NLP, and Neural Networks using TensorFlow and Keras, as well as CNN and its components. With your deep understanding of Data Science, you can work on projects in any industry of your choice within an organization.
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About the Certification Exam
The AEC certification exam for Data Science- Advanced comprises 60 questions and has a duration of 2 hours. It is an open-book exam featuring multiple-choice and true/false questions that assess knowledge across the major sections of Data Science- Advanced. The exam is graded out of 60 marks and is available for testing at more than 1,000 centers worldwide.
Requirements for the Exam
There are no prerequisites required for AEC Data Science- Advanced Certification Exam.
Requirements to pass the Exam
To successfully pass the AEC exam, candidates must obtain a minimum score of 40%.
What is the fee for the certification exam?
The exam registration fee is 100 USD
How to prepare for the Exam?
Individuals aspiring to take the Data Science- Advanced certification exam can prepare using AEC Syllabus. Additionally, they can enroll in the Data Science- Advanced training program provided by AEC Accredited Trainers and Partners to enhance their exam readiness.
- Basic Mathematics – DL
- Introduction to Perceptron & History of Neural networks
- Activation functions
- Leaky Relu
- Tanh f. Exponential Linear Units (ELU) g. Swish”
- Gradient Descent
- Learning Rate and tuning
- Optimization functions
- Introduction to Tensorflow
- Introduction to Keras, Theano, PyTorch – handson
- Backpropagation and chain rule
- Fully connected layer
- Cross entropy
- Weight Initialization
- coding perceptron
- Working with Images- Introduction
- Working with Images – Digitization, Sampling, and Quantization
- Working with images – Filtering – OpenCV
- Hands-on Python Demo: Working with images
- Introduction to Convolutions
- 2D convolutions for Images
- Convolution – Backward – handson
- Transposed Convolution and Fully Connected Layer as a Convolution – handson
- Pooling: Max Pooling and Other pooling options – practical
- CNN Architectures and LeNet Case Study
- Case Study: AlexNet
- Case Study: ZFNet and VGGNet
- Case Study: GoogleNet
- Case Study: ResNet
- GPU vs CPU
- Transfer Learning Principles and Practice
- Hands-on Keras Demo: SVHN Transfer learning from MNIST dataset
- Transfer learning Visualization (run package, occlusion experiment)
- Hands-on demo -T-SNE
- Hands-on CNN nets
- Hands-On OCR, Face Recognition, Object Detection, Pose Estimation, 3D estimations
- CNN’s at Work – Semantic Segmentation
- Semantic Segmentation process
- U-Net Architecture for Semantic Segmentation
- Hands-on demo – Semantic Segmentation using U-Net
- Other variants of Convolutions
- Inception and MobileNet models
- CNN’s at Work – Object Detection with region proposals
- CNN’s at Work – Object Detection with Yolo and SSD
- Siamese Network as metric learning
- How to train a Neural Network in Siamese way
- Hands-on demo – Siamese Network
Data science is the process to draw information from raw data and interpret it into useful insights for business decisions. Data Scientist, Data Analysts, Statistician, Data Engineer are a few of the common job profiles in Data Science. Data science involves a life cycle; capture, maintain, process, analyse and communicate data for business decisions.
Data Science is a comparatively new field with more jobs to offer than the existing fields in computer science and IT. Data Science is a vast multi-disciplinary field with scope of working in leading industries like healthcare, telecommunication, cyber security, finance and others. Data Science has grown with advancement in technology and has more scope of growth in future, offering unaccountable jobs in top MNCs and in top cities.
Any professional belonging to IT, marketing, engineering or software can take a data science course to pursue a career in the fields of data science. Undergraduate students, with more than 50% marks in mathematics, statistics or computer science in 12th examination from science stream are eligible. Graduates with a bachelor’s degree in science, engineering, technology or mathematics are also eligible.. Graduates in business studies like BBA or MBA are also eligible. Data science requires knowledge of mathematics, computer science and statistics.
Data Science certification enables you to start or elevate a career in the fields of data science. Some benefits are:
- Enhanced skill sets to work on different domains.
- Opportunity to work in leading industries.
- Flexibility to switch domains.
- More job opportunities to choose from.
- Higher salaries offered.
- Infinite job opportunities due to high demand.
According to an article published in naukri.com, 3,00,000 plus data scientists would be required in different sectors by 2024, with 3400 positions increasing every month. Common job profiles are:
- Data Scientist
- Python Programmer
- Machine Learning Engineer
- Data Analyst
- Data Engineer
Data Science course with Anexas focuses on training individuals on understanding of Data Science and its aspects, tools and techniques required and skill sets required. The course prepares students for job opportunities with many assignments and real-time projects. Key learnings after completion of this course:
Basic Course in data science: Data analysis, basic visualisation and data modelling.
Intermediate Course in data science: SQL, NLP and different statistical NLP techniques.
Advanced Course in data science: Neural Networks using TensorFlow and Keras, CNN and its different parts.
Yes. The course cost includes the cost of examination, certification, tools, software study material etc. There are no other costs payable once you pay for the course.
Anexas offers the following payment methods:
- Net Banking.
- Card Payment.
- Cash payment.
Cancellation is available 72 hours before the start of the course with 10% deduction. Any cancellation after that is non refundable.
However, Anexas supports custom batches or changes in time and date according to individual preferences, without any additional cost.
Anexas certification course includes all industry level requirements to work in the fields of Data Science. Including tools, softwares, skills and concepts used in different industries. The course opens you to opportunities available in different domains, with job assistance, project guidance, assignments and resume building.
How to prepare for the Exam?
Candidates who pass the exam will receive AEC Data Science- Advanced Training Certificate with lifetime validity. The certificate does not require any renewal. It will be issued in the form of a softcopy* (PDF), which includes a Certificate Code, a Verification Link, as well as the date and time of certification issuance.
*If a hardcopy certification is desired, shipping charges will be applied.