The course covers in depth knowledge of various Machine Learning techniques using Python, detailed understanding of supervised machine learning concepts, hands-on over various regression techniques in Python, application of learning theory functions in Python, detailed understanding of unsupervised machine learning concepts and its application in Python, hands-on over various clustering methods, dimensionality reduction and Kernel methods in Python, application of reinforcement machine learning concepts and adaptive control using Python, detailed understanding of Neural networks and advanced topics like advanced neural networks and convolutional neural networks and their industry application.
- Extraction, transformation, scraping, joining and cleaning of large data sets
- Analyse large data sets to bring out insights to solve business problems
- Use machine learning libraries and apply established machine learning algorithms in Python
- Hands-on knowledge on Machine learning concepts in Python using problem solving approach by working on real time cases and in class programming assignments
- Develop code in support of Machine learning solutions in Python
- Evaluation and debugging of various learning algorithms
- Detailed understanding and application of advanced machine learning concepts
Introduction to PythonModule 2:
Sequences and File OperationsModule 3:
Deep Dive – Functions, Sorting, Errors and Exception, Regular Expressions and PackagesModule 4:
Object Oriented Programming in PythonModule 5:
Debugging, Databases and Project SkeletonsModule 6:
Statistics - Machine Learning PrerequisitesModule 7:
Machine Learning using Python – EssentialsModule 8:
Data Analysis and Machine Learning - Deep DiveModule 9:
Scalable Machine Learning using SparkModule 10:
Web Scraping in Python and Project Work
All our instructors have industry experience and extensive functional expertise in the fields they train. They are handpicked and trained to deliver a great online learning experience.
- The assessment will be done on the basis of an online test and Project Evaluation at the end of the course.
- Weightage of Project Evaluation is 30% and that of Online test is 70%. Minimum pass percentage for online test is 70.
- On completion of the Assessment (Project + Test) with a minimum of 70% marks, training.com will issue a certificate of successful completion from NIIT.
- Five re-attempts will be provided to clear online test in case the candidate scores less than 70%.
- A Participation certificate will be issued if the candidate does not score 70% in the Assessment.
- Soft copy of the certification will be issued to the participants, on completion of the course.
To join this course, the aspirant should have the knowledge of Python programming language.
What is the Case Study based Project which I need to develop as part of this program?
NETFLIX MOVIE RECOMMENDATION ENGINE: Recommend movies to the netflix users or viewers based on their liking taste or coming with an innovative approach to suit their taste of movies
COPENHAGEN AIRPORT FLIGHT DELAY PREDICTION:Based on the flight stats available go to the root cause and figure out the reason for a flight delay and the delay prediction
SENTIMENT ANALYSIS OF A POLITICAL CAMPAIGN BASED ON TWITTER REVIEWS:Based on the twitter reviews of a product or a campaign conduct sentiment analysis of the data available
Who should join this course?
- IT professionals looking for a career switch into machine learning, data sciences and artificial intelligence
- Software developers looking for a career switch into machine learning, artificial neural networks and artificial intelligence
- Professionals working in machine learning and NLP
- Graduates with Python programming knowledge looking to build a career in machine learning
- Anyone with Python programming knowledge and a genuine interest in the field of machine learning
- Experienced professionals who would like to harness machine learning in their fields
Why should I join this course?
Owing to the huge demand for Machine Learning professional against scarcity of professionals in this field, Machine Learning has become top notch lucrative career option with impressive salary packages both inland and abroad. If you are seeking high career rise with promising future and heavy pay package then this course is a must for you.
What happens if I miss a session?
All the live sessions are recorded and available for later view. Learners can refer to recordings of a missed session at their convenience.
Where can I find my session schedule?
The session schedule will be available in the training.com Student portal - Learning Plan section. You can login to your training.com account to view the same.
Do you provide any study materials?
The study material will be available in the training.com Student portal - Resources section. You can login to your training.com account to view the same.
What is your refund policy?
Upon registering for the course, if for some reason you are unable or unwilling to participate in the course further, you can apply for a refund. You can initiate the refund any time before start of the second session of the course by sending an email to firstname.lastname@example.org , with your enrolment details and bank account details (where you want the amount to be transferred). Once you initiate a refund request, you will receive the amount within 21 days after confirmation and verification by our team. This is provided if you have not downloaded any courseware after registration.
What are the minimum system requirements to attend the program?
- Personal computer or Laptop with web camera
- Headphone with Noise Clarity Microphone
- Broadband connection with minimum bandwidth of 4 mbps.
- Its recommended to use System Health Check to examine the OS details, Add in, Plugins, Camera, Mic and other external devices.
Minimum system requirements for accessing the courses are:
Is there an official support desk for technical guidance during the training program?
Yes. For immediate technical support during the live online classroom sessions, you can call 91-9717992809 or 0124-4917203 between 9:00 AM and 8:00 PM IST. You can write to email@example.com for all other queries and our team will be happy to help you.