I started masters program in data analysis/science. How do I allocate my time?

I'm from EU and im on my first semester of 2 year masters program in data analyst/science. A lot of students, including me, come from non technical bachelor's. I come from accounting so most concepts introduced here are new to me and continuation for some. University is aware of the problem and I feel like program was dumbed down a little or requirements to pass a class were lowered

Knowledge from my degree is completely useless here. We did have linelar algebra, calulus, stats, econometrics but I forgotten it or it just was easy to pass. Only skills I think I retained is group work, communication, presenting, solving business problems.

As for my curret program:

|| || |Subject Name|Lectures (L)|Classes/Labs (C)| |Python and R in Data Analysis (from 0)|0|30| |IT Support for Processes and Projects (SAP&ABAP)|15|15| |Financial Analysis|15|15| |Modeling of Economic Processes |15|15| |Dynamic and Financial Econometrics ( R )|15|15| |Business Decision Making Methods|15|15| |Actuarial Methods|15|15| |Optimization Models in Data Mining|15|15| |Business Game|0|15| |Multivariate Statistical Analysis|15|15| |Business Intelligence|15|15|

|| || |Subject Name |Lectures|Classes/Labs| |Methods of Measuring Economic Organization Efficiency|15|30| |IT Tools in Research Applications|0|30| |Modeling Dependencies in Economic Data|15|15| |Fair Division Methods|15|15| |Work Process Analysis|30|0| |Monetary Policy|30|0| |Management Accounting and Controlling|15|15| |Mathematical Economics|15|15| |Analysis of Financial Instruments|15|15|

|| || |Subject Name|Lectures|Classes/Labs| |Applications of R and Python in Data Science|0|30| |Visualization of Data and Analysis Results|0|30| |Econometric Tools in Data Analysis|0|30| |Data Mining Techniques|0|30| |Big Data|0|30| |Machine Learning Methods|0|30|

My end goal (or more like a wish) is career in data science/ML

I doubt that simply passing these classes will be enough to learn enough to get me hired, but on the other hand Multivariate Statistical Analysis was draining and required my full attention to grasp since i was starting from a position of getting used to reading formulas and theacher was flying through the thing.

I was lost during classes & lectures but in the end it only required 3-4 hours daily for 10 days prior to exam to end up solving every problem on a test sheet - either exam was really easy or there was not much to learn anyway

So that's what i'm dealing with here. It's the combination of low requirements to pass while still providing a nice chunk of material to go through for someone on my level

I'm just having hard time deciding how to allocate my time, what % of it to spend on grapsing study material and what part of it should I spend on skills that will get me hired (and what to focus on?). SQL for example will not be covered as it was part of bachelor's program.

Currently we are on:

Python and R in Data Analysis (from 0, focus on python)

IT Support for Processes and Projects (SAP&ABAP)

Dynamic and Financial Econometrics ( R & some theory i need to get through )

And besides that I have a strong feeling that ASAP I need to dive into stat books/courses to expand my knowledge beyond things like anova, contrast analysis and bunch of other parametric/non parametric tests