Why Machine Learning?
Every organization is betting big on machine learning to fuel their growth and the demand for data scientists has skyrocketed. Machine Learning is not only the most lucrative career option today (average salary for Data Science roles in India is 10LPA+ as per Glassdoor) but will soon become an essential skill for everyone. Hence investing time and effort to learn Machine Learning will give every student a competitive advantage when they step out in the job market tomorrow.
What will I learn?
- 1. Introduction to Machine Learning
- 2. Python for Machine Learning
- 3. Machine Learning Life Cycle
- 4. Data Exploration and Manipulation
- 5. Data Manipulation and Visualization
- 6. Build Your First Model
- 7. Evaluation Metrics
- 8. k-NN
- 9. Selecting the Right Model
- 10. Linear Models
- 11. Decision Trees
- 12. Feature Engineering
- 1. Welcome to the Applied Machine Learning Course
- 2. Basic Ensemble Model and Advance Ensemble Techniques
- 3. Hyperparameter Tuning
- 4. Dimensionality Reduction (Part I)
- 5. Working with Text Data
- 6. Naïve Bayes
- 7. Support Vector Machine
- 8. Working with Image Data
- 9. Advance Dimensionality Reduction
- 10. Unsupervised Machine Learning Methods
- 11. Automated Machine Learning
- 1. Introduction to Databases
- 2. Installing MySQL/ MariaDB
- 3. Getting started
- 4. Modifying Databases structures
- 5. Importing and Exporting Data
- 6. Data Analysis
- 7. Real-Life Project - Descriptive Analytics of FIFA 19 Players
- 8. Getting Data from Multiple Tables
- 9. Introduction to Indexing
- 10. MySQL built-in functions
- 11. Manipulate MySQL from Python
- 1. Overview - Ace Data Science Interviews
- 2. Overview - The 7 step Data Science Interviews process
- 3. Step 1 - Understanding roles, skills, Interviews Framework
- 4. Step 2 - Building Your Digital Presence
- 5. Step 3 - Building Resume and Applying for Jobs
- 6. Step 4 - Telephonic Interviews
- 7. Step 5 - Assignments
- 8. Step 6 - In-Person Interview(s)
- 9. Step 7 - Post Interview Follow-ups
Who will be my teachers?
How will I learn?
What projects will I build?
How will my doubt get solved?
What placement assistance will I receive?
Enrollment Form
Q. Who is the specialization for?
The Machine Learning Specialization is for:
(i) Pre-final year or final year college students who are eyeing for campus placements or jobs in the field of Data Science
(ii) Recent graduates and working professionals who want to build a career in or switch career fields to Data Science
(iii) Early-year college students who want to specialize in the ever-growing world of Data Science to get a head start
Q. The specialization fee feels high. Is it worth it?
The specialization is meant for serious learners who are motivated to build a career in Data Science and are willing to invest the required time and money for it. The average salary for Data Science professionals in India is 10LPA+, compared to that specialization fee is a small investment with great returns.
It is also important to note that Specialization consists of 4 trainings (and not just one training), 8 projects, and one-on-one mentoring from a practicing data scientist and the fee is decided accordingly.
Also, if a one-time payment of specialization fee is not feasible for you and you would like to break it in monthly payments, please write to us on trainings@internshala.com.
Finally, if you are a beginner who would like to explore the subject and build a basic understanding first before making a larger commitment to the specialization, please check our Introduction to Machine Learning training meant for beginners here.
Q. What does placement assistance mean?
The placement assistance for Machine Learning Specialization consists of 3 components -
1. A 30 minutes phone call with a practicing data scientist for you to get career guidance
2. Access to curated Machine Learning internships & fresher jobs on Internshala for you to apply to
3. One-on-one mentorship from an experienced data scientist for you to regularly clear your conceptual and career-related doubts
These 3 components clubbed with the knowledge and practice you would gain in the specialization are sufficient for you to kickstart your career as a Data Scientist.
Q. Why is the specialization six months long?
The specialization is self-paced which means it entirely depends on how much effort you put every day in learning the syllabus. Those who are ready to put in extra hours can complete it before six months also.
However, it is worth noting that the specialization comprises of 4 trainings and for you to learn all the concepts (beginner level to advanced) properly would take time and hence you should be prepared to invest required effort to get the desired outcome.
If you are looking for a short duration program to explore the subject first, please check our Introduction to Machine Learning training meant for beginners here.
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