DATA SCIENCE with MACHINE LEARNING


data science training in Pune

COURSE OBJECTIVE

1. Learn the machine learning from Scratch

2. Provide a right guidance for persons who are seeking to enter in the world of machine learning and data science.

3. Take people from novice to expert in machine learning without compromising on important concepts, within 7 weeks.

4. Learn python programming which is emerging as the top programming language for doing machine learning and data science

5. To be able to design, develop and test various machine learning models.

5. Learn the important techniques which are used in industry (Skills in demand)

- Learn foundation of Data science and Machine learning which is mostly the difficult part to start your career in this field

- learn the recommendation techniques. In today's time the most of the revenue is generated using the recommendation algorithms than any other algorithms. It is required for most of the clients in the industry today. Google and Amazon may have self-driving cars but their core revenue is generated through these kinds of algorithms.(currently no other training institutes are offering these techniques in syllabus)

6. Learn Neural networks basics with hands on.

About the Data Science trainer

Trainer is a working professional with 5 years of experience and currently working as a Data Scientist in a MNC. 
 
Over the years while working as data scientist, he got exposure on all aspects of data science for example data gathering from various sources, data cleansing, data test and analysis, designing algorithm, fine tuning algorithm, presenting analytics to business for decision making etc.
 
He has worked directly with solution architect to help create recommendation engines for clients from industries like digital marketing, retail and E commerce.
 
 
 Trainer's exposure on Data Science and Machine Learning
-    Analyzing business problem statement and designing it into data science/ machine learning use case.
 
-    Worked on various POC (Proof of concept) for clients
 
-    Designing/ documenting key requirements for each components of the solution architecture.
 
-    Gathering data from various sources.
 
-    Proficiently identifying and applying appropriate data analytics algorithm. For example: Unsupervised learning- Clustering, factor analysis, association rule mining. Supervised Learning: Classification, Neural Nets, Support Vector Machines, Regression etc.
 
-    Presenting the result of data analysis to business for decision making ie. Data visualization

Hands on training along with project:

Training is going to be a mix of theory as well as practical.

We totally understand the importance of hands-on experience. Hence special emphasis is given to practical. Initially trainer explains the concepts and demonstrates the same.  Later on students is expected to perform certain task under the guidance of trainer.

As a part of training, students will work on project under the guidance of trainer. One of the project will be on NLP (Natural Language Processing) to help students understand machine learning better.

We work really hard with our students and we do expect students also to put equal efforts. Students are expected to practice as much as possible and raise questions/ doubts with