Harry Potter
Scaler Data Science Oct2021 (Intermediate) course includes real-world projects in partnership with top companies, 1:1 mentorship, placement assistance, and learning of essential tools and skills like Git, TensorFlow, and Big Data. The curriculum covers Python libraries, Probability and Applied Statistics, Data Acquisition, EDA, Product Analytics, and more. Enroll now to become a certified Data Scientist or ML Engineer
1.
What sort of Data Science projects are incorporated as a feature of the course?
Projects from top organizations to make you a genuine Data Researcher or ML Engineer.
Get hands-on experience by working with genuine data sets, on projects worked in associations with top organizations
2.
Consider the possibility that I stall out or require direction.
Get 1:1 Mentorship from Master Data Researchers and ML Engineers!
Talk 1:1 with your coach to get every one of your questions and questions responded to, assist you with characterizing your vocation ways, conduct mock meetings, and give you point by point input.
.
Will I get Position Help?
Make genuine contact with your new range of abilities!
Organizations wish to enlist data researchers and ML engineers who are confirmed and gifted as well as have a profound comprehension of business. We at Scaler assist you with accomplishing the best range of abilities and assist you with landing position opportunities from top organizations
4.
Which Data Science devices could I learn?
"Git" better at foreseeing and controlling data with a variety of instruments!
Learn 45+ devices, including Git, TensorFlow, PySpark, PyTorch, Kafka
5
Could I at any point gain one of a kind abilities from this Data Science Course?
Turn out to be exceptionally knowledgeable with DS and ML Exploration.
Figure out how to peruse significant Exploration Papers in DS, ML, Profound Learning, and get legitimate direction to Distribute Exploration Paper in Worldwide conferences
8.
For what reason do I have to learn DSA and Big Data?
To assist you with doing successful problem solving and pursue more intelligent business choices
Besides, DSA and Big Data are fundamental abilities in your tool stash to sparkle in your jobs as a Data Researcher or ML Engineer.
Educational program
Python libraries
Numpy, Pandas
Matplotlib
Seaborn
Data Acquisition
Web API
Web Scraping
Beautifulsoup
Tweepy
Probability and Applied Insights
Probability
Bayes Theorem
Distributions
Descriptive Insights, anomaly treatment
Confidence Interval
Central cutoff theorem
Hypothesis test, Stomach muscle testing
ANOVA
Correlation
EDA, Feature Engineering, Missing worth treatment
Experiment Design
Regex, NLTK, OpenCV
Product Analytics
System to address product sense questions
Diagnostics
Metrics, KPI
Product Design and Advancement
Guesstimates
Product Cases from Netflix, Stripe, Instagram
High level Python
Python Boost
Nuts and bolts of Time and Space Complexity
OOPS
Functional Programming
Exception Handling and Modules
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