Dual Certification Machine Learning Training and Internship Program
In this program, students will learn Machine Learning For Data Science from scratch. Which includes 10+ tools machine learning tools. Participants will be introduced to 3 Case studies with 1 Project and it also comprises of Internship work.
Students Trained so far
Instructor Led Program
Industrial Case Studies
Customized Tracks For Better Results
Python, Statistics & tools
In this track, Participants will be understanding the basic concepts of Machine Learning and Data Science life cycle and complete understanding on Python, Statistics and working with Google collab and jupyter.
Machine Learning and Algorithms
In the second stage participants will be working on Anaconda platform to perform machine learning operations on chose data sets and will be introduced to many tools.
Poject, Case Studies and Assessments
In the third stage, Participants will be exposed to industrial case studies and application of machine learning in different domains. It also includes Project work and assessments.
Top skills you will learn
Data Processing, Statistics, Python Libraries, Machine Learning Algorithms, Tools like Anaconda, Jupyter, Google Collab and many more.
After completion of the program, Participants will be connected to the alumni network and Job opportunities will be notified.
Who can enroll for this programs ?
Freshers, Undergraduates, Employees planning to switch their career. Who else are looking for professional work experience of one month.
Should be a student or Fresher or Employee planning to switch career to Data Science. With basic python programming and math fundamentals.
Syllabus & Modules
Our curriculum suits the requirement of the industry
- Introduction to Jupyter and Anaconda
- Jupyter Notebook and google collab
- Python for data science part-1
- Python for data science part-2
- Data visualization techniques
- Assessment – 1
- Assignment & Group Discussion -1
- Machine Learning Basics.
- Introduction to Statistics for Data Science
- Statistics for Data Science part-2
- CLT Theorm
- Gradient Descent
- Assessment – 2 & Assignment – 2
- Guest Lecture – 1
- Linear Regressions Concepts Part-1
- Linear regressions Part-2
- Logistic Regressions
- Maximum likehood
- Decision Tree
- Assessment – 3
- Assignment – 3
- Bagging and Boosting
- Explanation of Model
- Ensemble Modelling
- Case Study -1
- Case Study – 2
- Case Study – 3
- Project Work Validation
- Final Assessment & Certification
What Our Students Have to Say
Meet Our Instructor
Mr. Tushit Dave, Data Scientist at International Institute of Engineering. Mr. Tushit is an high end Data analyst worked with more than 6+ MNC’s and worked on 15+ Industrial projects till date.